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John Jantsch (00:01.371)

Welcome to another episode of the Duck Tape Marketing Podcast. This is John Jantsch. And my guest today is Steve Cunningham. He’s a former agency owner, startup founder, and now AI native business strategist. He built a successful book summary platform called ReadIt.ForMe, backed by billionaire investor, read a book a day for 10 years. I feel like I do that sometimes. But when AI disrupted his industry, it nearly wiped him out. So now he coaches.

Steve (00:01.71)

I’m to you to sign up for the presentation. I’m ask you to for the I’m going ask to up for I’m going ask sign up for I’m you to I’m to ask you to I’m going you to sign up presentation. I’m going to sign the presentation. I’m going you to going I’m

John Jantsch (00:30.425)

solo consultants, agency owners, and service professionals to make more money faster and easier by becoming AI native through his company, Simple and his brand new book, the AI native full stack consultant. So Steve, welcome back to the show. I say welcome back. think this is your first time actually on the show, but, you and I tried to record and I was like in a hurricane and it didn’t work out. so I’m glad you were able to come back.

Steve (00:31.822)

Thanks for having me, John.

Steve (00:56.622)

Good to be back for the first time.

John Jantsch (00:58.683)

So, I mentioned the AI destroyed your business. You want to talk a little bit about it or tell that story as I’m sure you have a number of times.

Steve (01:08.75)

Yeah. So read it for me was a business that I hoped would last the rest of my life. I loved that business. I like to joke if I could get in the time machine, travel back to 2022 and destroy all the AI, I would do it. That’s how much I love that business. I got to read books from my favorite business authors like yourself. I live here in San Antonio, Texas by the Riverwalk. I would literally go outside.

John Jantsch (01:24.283)

Ha ha ha.

Steve (01:37.134)

I would take my, I would read on the phone. So I read Kindle on the phone and that was my job. Uh, so I loved it. And so when Chad GPT came out, um, you know, this is a content business, right? So it would take me about eight hours to read a book and summarize it, take notes and do all the, all the stuff from beginning to end. And when I realized that you could get a passable book summary, which is by asking for it and maybe, then with some good prompting.

get a finished product in much less way less time than it would take for me to read and summarize the book. I knew that we were in trouble. so it didn’t happen overnight. We still have people reaching out wondering, can they bring Rita for me into their business? I, two and a half, three years later, it baffles me that people still have not figured out that they don’t need us anymore for that. But

John Jantsch (02:31.579)

you

Steve (02:34.478)

Yeah. So the revenue went down, not overnight, slowly but surely. And so we realized that we had to do something about that and saw the writing on the wall transformed our operations with AI. Then lots of folks wanted to know how we were doing it and started showing them. And here we are two and a half years later and we’re fully AI native and doing lots of fun and exciting things.

John Jantsch (03:01.231)

So I suspect, maybe I’m wrong, maybe I’m naive, but that most marketers today are consultants have figured out, know, yeah, I need to use this AI thing. You use the term AI native full stack consultant. How does that differ from someone who say just uses it in their workflows?

Steve (03:18.798)

Well, one of the things that has happened in the last few months is that the easiest way to put it is the AI has gotten really good. So there was this, we were on a short timeline for the podcast. We don’t have time to dive into it deep, but there were studies done through OpenAI. So take that with a grain of salt, but it’s called the GDPVAL. And what they did was they took…

bunch of subject matter experts. got a bucket of tasks across most knowledge work. And they said, give us your best blank. And there would be a task. And so they would do it. And then they would have the AI do the exact same task. And then they would give it to another subject matter expert. And they would say, which one of these is better? And so 2024, wins or ties by the AI was like a 10%. Now it’s a caveat that the AI has all of the context it needs in order to do

the job. And most people don’t get anywhere close to giving the AI all the best, all the contacts they need. So 10 % like people would say, yeah, it’s not a 10%. Well, it’s probably not a 10 % because you didn’t give it all the context. anyways, move forward into 2025, middle of 2025, we’re approaching 50 % wins or ties by the AI. So we’re getting close. We call that the AI tipping point. As of a couple of months ago, the wins and ties by AI were

John Jantsch (04:17.56)

Yeah, right,

Steve (04:42.414)

70 % and since then you can feel if you’re using AI, this is getting better and better and better. So what we mean by full stack consultant is if you understand what good looks like across any subject matter expert domain, you can get pretty close to doing an incredible job for your clients in all functional areas of a business. So a marketing agency can do

sales enablement, but they can also do some CFO work. They can do some strategy work. And that is what we mean by the full stack consultant. And the idea is that if you get very good at some new skills, which are not obvious to most people, like how to produce a really good, robust context library for your clients, you and the company can do amazing work. It can be done.

John Jantsch (05:15.385)

Mm-hmm.

Steve (05:41.166)

incredibly quickly and we’re learning more and more every day about what that looks like. So today, this morning, I did about, and this sounds ridiculous when you hear it from the outside and I understand that it sounds ridiculous, but I did about, in about two hours with 30 minutes of my work and an hour and half of just waiting around for the AI to finish its work, about 260 hours of design, interface work, copywriting.

and development. I don’t do any of those things in the past life. I have no skills in those things, but I know what to ask for. I know what I want and I know what good looks like and now I can get it. So it’s an amazing time that we live in.

John Jantsch (06:14.232)

Mm-hmm. Yeah.

John Jantsch (06:24.731)

I want to go back to a point you made there because, I have jokingly, but seriously said, you know, marketing is everything. And what I really meant by that was in a lot of small businesses, I would go into, there were a lot of things I had to fix that weren’t under the, you know, the heading of marketing a lot of times, because if marketing was going to work or we were going to grow the business, I had to get involved in this area over here. Sales was a typical one. Customer service is another one that, know, that you don’t always hire a marketing agency for.

But I would get into it out of necessity. And I think what you’re really pointing to is a great point, this idea of, you go into a business, it’s not just a matter of offering a suite of like, what do you need? It’s more like I can be more effective at doing my job that you hired me for if I can actually easily fix an area over here that I may not have true expertise in, or I couldn’t spend the time because I wasn’t being paid to fix their P &L, for example.

so I think that’s a great point. Let me back up again, because I I circled, I wanted the word context. that, let’s spend a little time talking about that. Cause I think AI has gotten better, but I also think prompters are getting better. and we’re realizing, you know, we get better output with, context. how do you give a, how, how in your view is probably a really long answer. How in your view, do you give AI the proper context?

Steve (07:52.408)

So when most people talk about context and there’s a term called context engineering, they’re mostly talking about it in the terms of like a single task that’s going on. What we mean by context engineering is how does the AI know everything about your business? that whenever you pull up a task to do that you actually, the AI can, it’s really hard to explain without getting into the weeds, but here’s my best shot.

John Jantsch (07:58.512)

Mm-hmm.

Steve (08:22.668)

So imagine that you have like the world’s best employee on every single task that could be done in your business, but they have amnesia. Every single time you give them a new task, they know nothing. So you have to train them. And that sounds like a really painful thing to have to do. But if you build a context library and only has to be done once to start, you can train that, you can give that AI like,

10 years of training in about 10 seconds. So it forgets all the time, but it learns like years in seconds. So all you gotta do, like this is how I boot up my instance of how I’m AI in my world as the CEO of our company. I onboarded the AI, I go look at the, I literally create an onboarding file. I say, go look at the onboarding file and get yourself onboarded. And 10 seconds later, it knows exactly like,

John Jantsch (08:54.629)

Mm-hmm.

Steve (09:20.418)

from a meta perspective, how we’re going to do our work today. And I’ll say, go look at that folder and let’s do this task, like redesign our interface for this page in our system. And knows exactly how I like to work. It knows exactly how I want design options. And as a marketer, you’ll appreciate this. you can go in and you’re doing, let’s say you’re doing ad variations. You go and ask for

You don’t even have to be that specific. If it knows everything about your business, you just say, give me five ad variations on this one topic or this one offer we’re making. Sends it back. You look at it. You’re like, like that one the most. And I’ve had the AI give me like the rationale for like, is scored it and ranked it. Then I could give me five more variations on that one. And then five more on that one. And one of the things that’s not obvious to people is that the cost of variations is almost zero.

John Jantsch (10:05.177)

Mm-hmm.

John Jantsch (10:10.768)

Right.

Steve (10:17.58)

So you can ask for an infinite number of variations of.

John Jantsch (10:17.594)

Yeah.

Yeah, I do that with subject lines for emails. mean, same thing. It’s like, kind of like the idea of this one. Iterate on that 10 more times. Yeah.

Steve (10:27.31)

Yeah, but you can do it for really big things too. So it’s not just like a single subject. You can do it for an entire interface, like an entire set of code. so like, because it works so fast and the cost of its work is so low, it transforms the way you approach the work. so customizing campaigns down to the individual level, not a problem anymore.

John Jantsch (10:31.193)

Yeah, yeah. Right.

Mm-hmm.

Steve (10:57.25)

Like I can find your LinkedIn profile, can scrape it and I can send you like an entire landing page that’s speaking directly to you. And it cost me a penny to do. And so there are things that we can do that were quite literally impossible before that now makes sense.

John Jantsch (11:16.543)

This might be good time to talk platforms and technologies a little bit. Are you agnostic or have you really gone all in and maybe it’s so complex that you can’t really say it in one sentence, but is like, are you a Gemini person? Are you a Chad’s EBT person or have you really building your own stuff?

Steve (11:36.942)

We’re definitely not building our own stuff. We have a very particular point of view, which is we’re serving companies and companies will eventually choose their LLM of choice. And that’s what they’re going to do all of their work on. So we are, we’re not hitching our wagon to any one LLM. We also have the point of view that for the most part, most AI rappers go away. So an organization is going to build their own software.

John Jantsch (12:01.679)

Yeah, yeah, yeah.

Steve (12:06.894)

So that’s our long-term bet. And so we’re just using whatever one is most productive. I personally have the max subscription on Claude, OpenAI and Gemini. I’m mostly using Claude right now because Claude Cowork and Claude Code just came out. And so if you listen to this like a month later, maybe I’m on something else by then, but Claude Cowork has been that tool alone.

John Jantsch (12:28.558)

You

Steve (12:33.548)

has transformed our operations in two weeks. Like we literally operate day to day differently now because of that tool. So, whatever one’s working the best when the next time we talk is the one we’ll be on then.

John Jantsch (12:36.346)

Yes.

John Jantsch (12:45.349)

Yeah.

Yeah. You know, I contended for a long time that just what you said, it’s, it’s going to be plumbing. It’s not going to be, Oh, I use this tool or that too. It’s going to be, no, this already works with what I use. And I really feel like, doesn’t that give Microsoft and Google because of their installed user base? mean, you know, I fire up Gmail and all of a sudden it’s like, Oh, there’s a new tool. Um, you know, I can opt into, you know, I mean, doesn’t that give them an advantage? And also I think the other thing, the first version of AI tools.

Is there better kind of use them by themselves? Well, now all of sudden we got collaboration built in, which I think was a big missing part. And so it’s like working the way people work already.

Steve (13:27.214)

Yeah, I think the like all other things being equal, Microsoft and Google have the biggest moat around it. However, for the longest time, Chad GPT was the best tool. And now Claude is by far the best tool. so I would have thought that if it was true that Microsoft and Google would be like for sure would win, it would have happened.

John Jantsch (13:34.372)

Mm-hmm.

John Jantsch (13:51.525)

Yeah, yeah, yeah, yeah.

Steve (13:52.224)

I know because they had not only they have the user base, they have all the documents and that’s, that’s what the AI needs for context. But as it turns out, the AI does not read and work with the file formats that we all produced over the last 20 years, which was PowerPoints and Word documents and all of those kinds of things. So there’s, there’s going to be a shift around that as well, which I think will loosen.

John Jantsch (14:08.995)

the

Steve (14:18.382)

the moat that they have because we’re not going to be stuck on PowerPoint anymore. Like I, the, in the last couple of weeks, I’ve been on this kick of, and I think this is just true. I will never use keynote or PowerPoint ever again. Um, and I’m not using like another AI tool. just build HTML documents and it does exactly what I want. And I, that’s my presentation style. Um, we do SOPs in our business. Everybody in our company builds HTML.

John Jantsch (14:32.155)

Mm.

Steve (14:46.132)

S O P S because you can just speak into a computer. HTML files open everywhere. And it’s also a good language for the LLMs to understand because it’s way easier to read than, than a PowerPoint. There’s others. If you pay attention to how software engineers are using AI, you’ll have a, you’ll have a glimpse of the future. They’re mostly using file formats that they’re comfortable with and that are, that work well for.

John Jantsch (14:57.147)

yeah.

Steve (15:15.182)

development, like markdown files and things like that. So that’s what you’ll see them suggest. Like you have to use markdown files for these things. And, what our point of view around this, and I think this will just prove to be true is that we need to be building like artifacts or deliverables, whatever you want to call it for humans and AI, not just humans. Like humans only is like PowerPoint, like LLMs hate PowerPoint. I hate word document.

John Jantsch (15:17.722)

Yeah, yeah, yeah.

John Jantsch (15:43.201)

can’t can’t can’t read them at all.

Steve (15:44.878)

There’s so much code around it, right? So then you have the like markdown files and things that most humans they look at it. Like I can’t, I can’t, a picture is worth a thousand words. It’s a real thing. Like we need to see visuals and workflows and all those things. And so HTML happens to do both of those incredibly well. So whether or not we’re right on that, I don’t know, but for now it’s like transforming the way that we do work because we can now.

build things that both our humans understand, the LLMs understand, and also there’s this magical thing that happens when a non-technical person speaks a website into existence, and just presses a button and it’s live. So it’s also a really good AI adoption tool, because it’s cool, right? Like it’s cool to like, you build something beautiful. So as a marketer, if you have a design system,

Most companies would never spend 30, 40, $50,000 on. You can speak one of those into existence. Like you can do it right now. Then everything that gets designed looks great in your company. And now everybody’s sharing beautifully designed. SOP documents. Like that’s, that’s a weird thing to think about, but it’s like, I like doing it. It looks nice. it explains what I explains my thoughts and my process. And so, yeah, I think, I think this year is going to be.

transformative in how we all do work and I don’t think it’s going to look the same by the end of the year.

John Jantsch (17:17.11)

So, and I know you have an answer for this, but this, I’m guessing listeners are out there going, okay, if I can just speak this stuff into existence, am I going to just start creating stuff without any kind of guardrails and without any human intervention? where’s the, you know, the pushback you’re getting from people that hate AI. So imagine the people that love AI, but don’t want to be embarrassed.

Steve (17:43.31)

What do you mean by guardrails specifically?

John Jantsch (17:46.123)

just, just meaning like, if I can design all these things, who’s going to actually go and make sure that they’re, they’re being done right. That they look good, that they say what they’re supposed to say. Cause you know, some of, particularly some of the image, you know, generates today. I mean, there’s, it’s just like appalling. Some of the things that show up in, in some of those.

Steve (18:06.478)

Well, I think there’s trying to figure out the 32nd way of answering this question. So the way we look at how work is done is by deliverables. you can look at it as a process, you can look at it as tasks, you can look at it as deliverables. But if you look at it as a deliverable, is that that’s when the thing ends. And that’s when the human has to look at it. It’s when the deliverable is done.

John Jantsch (18:18.864)

Right.

Steve (18:31.182)

First of all, should have the AI do a QC process on itself. You can do that. And it actually does a really good job of QCing its own work. So that’s the thing that most people don’t understand. But then once it comes off the press, whatever metaphor you want to use, and a human looks at it and says, are we sending this out? And if you treat it, and this is a language that most knowledge workers don’t like, it’s a factory now. And so you don’t QC every

energy drink can that comes off the line. But you look at some of them, right? And you know that if this one is this one’s off, well, we got to look at the ones that just went out the door because maybe they have a defect as well. So it becomes more of a factory mindset, knowing that if you if you have a good manufacturing process and that this again, like marketing agencies will hate this like, but that is that it but

John Jantsch (19:02.97)

Right.

John Jantsch (19:22.297)

Yeah. Yeah. Even the word factory there, they’re going to cringe at. Right.

Steve (19:26.894)

Like if you do not turn your marketing agency into a factory in 2026, you will be out of business. Like let’s go have a, we’ll do it next year and we’ll see whether or not that’s true. Like you have to, you’ll have to learn good workflows. You need to learn good work instructions. You need to learn good QC process. And so, and once you do, you can start mass producing things that are top notch and

John Jantsch (19:37.403)

Yeah.

Steve (19:56.138)

knowledge work will be turned into a factory. And then what gets layered on top of that is a new skill set, which is not 100 % clear what that is yet, but we will invent new things to do that will just add value on top of that.

John Jantsch (20:14.085)

Fascinating, Steve. Appreciate you stopping by the Duct Tape Marketing Podcast. Where do you want to invite people to find out more about, I think it’s simpleconsultants.ai and obviously about your book?

Steve (20:26.978)

Yeah, well, if you’re up for it, I would love to give everybody in your audience free access to our BlackBelt training. We’ll create a page specifically for your network. It’ll be roiassociation.ai.

John Jantsch (20:47.931)

Awesome. And we’ll put that in the show notes as well. So that was ROI.association, is that what you said?

Steve (20:54.824)

roiassociation.ai.

John Jantsch (20:56.973)

dot, dot A. Okay. Got it. Awesome. Well, as I said, we’ll put that in the show notes as well. So Steve, again, appreciate you stopping by. This is awesome. And hopefully we’ll run into you one of these days out there on the road.

Steve (21:11.662)

Absolutely. Thanks, John.

John Jantsch (00:01.371)

Welcome to another episode of the Duck Tape Marketing Podcast. This is John Jantsch. And my guest today is Steve Cunningham. He’s a former agency owner, startup founder, and now AI native business strategist. He built a successful book summary platform called ReadIt.ForMe, backed by billionaire investor, read a book a day for 10 years. I feel like I do that sometimes. But when AI disrupted his industry, it nearly wiped him out. So now he coaches.

Steve (00:01.71)

I’m to you to sign up for the presentation. I’m ask you to for the I’m going ask to up for I’m going ask sign up for I’m you to I’m to ask you to I’m going you to sign up presentation. I’m going to sign the presentation. I’m going you to going I’m

John Jantsch (00:30.425)

solo consultants, agency owners, and service professionals to make more money faster and easier by becoming AI native through his company, Simple and his brand new book, the AI native full stack consultant. So Steve, welcome back to the show. I say welcome back. think this is your first time actually on the show, but, you and I tried to record and I was like in a hurricane and it didn’t work out. so I’m glad you were able to come back.

Steve (00:31.822)

Thanks for having me, John.

Steve (00:56.622)

Good to be back for the first time.

John Jantsch (00:58.683)

So, I mentioned the AI destroyed your business. You want to talk a little bit about it or tell that story as I’m sure you have a number of times.

Steve (01:08.75)

Yeah. So read it for me was a business that I hoped would last the rest of my life. I loved that business. I like to joke if I could get in the time machine, travel back to 2022 and destroy all the AI, I would do it. That’s how much I love that business. I got to read books from my favorite business authors like yourself. I live here in San Antonio, Texas by the Riverwalk. I would literally go outside.

John Jantsch (01:24.283)

Ha ha ha.

Steve (01:37.134)

I would take my, I would read on the phone. So I read Kindle on the phone and that was my job. Uh, so I loved it. And so when Chad GPT came out, um, you know, this is a content business, right? So it would take me about eight hours to read a book and summarize it, take notes and do all the, all the stuff from beginning to end. And when I realized that you could get a passable book summary, which is by asking for it and maybe, then with some good prompting.

get a finished product in much less way less time than it would take for me to read and summarize the book. I knew that we were in trouble. so it didn’t happen overnight. We still have people reaching out wondering, can they bring Rita for me into their business? I, two and a half, three years later, it baffles me that people still have not figured out that they don’t need us anymore for that. But

John Jantsch (02:31.579)

you

Steve (02:34.478)

Yeah. So the revenue went down, not overnight, slowly but surely. And so we realized that we had to do something about that and saw the writing on the wall transformed our operations with AI. Then lots of folks wanted to know how we were doing it and started showing them. And here we are two and a half years later and we’re fully AI native and doing lots of fun and exciting things.

John Jantsch (03:01.231)

So I suspect, maybe I’m wrong, maybe I’m naive, but that most marketers today are consultants have figured out, know, yeah, I need to use this AI thing. You use the term AI native full stack consultant. How does that differ from someone who say just uses it in their workflows?

Steve (03:18.798)

Well, one of the things that has happened in the last few months is that the easiest way to put it is the AI has gotten really good. So there was this, we were on a short timeline for the podcast. We don’t have time to dive into it deep, but there were studies done through OpenAI. So take that with a grain of salt, but it’s called the GDPVAL. And what they did was they took…

bunch of subject matter experts. got a bucket of tasks across most knowledge work. And they said, give us your best blank. And there would be a task. And so they would do it. And then they would have the AI do the exact same task. And then they would give it to another subject matter expert. And they would say, which one of these is better? And so 2024, wins or ties by the AI was like a 10%. Now it’s a caveat that the AI has all of the context it needs in order to do

the job. And most people don’t get anywhere close to giving the AI all the best, all the contacts they need. So 10 % like people would say, yeah, it’s not a 10%. Well, it’s probably not a 10 % because you didn’t give it all the context. anyways, move forward into 2025, middle of 2025, we’re approaching 50 % wins or ties by the AI. So we’re getting close. We call that the AI tipping point. As of a couple of months ago, the wins and ties by AI were

John Jantsch (04:17.56)

Yeah, right,

Steve (04:42.414)

70 % and since then you can feel if you’re using AI, this is getting better and better and better. So what we mean by full stack consultant is if you understand what good looks like across any subject matter expert domain, you can get pretty close to doing an incredible job for your clients in all functional areas of a business. So a marketing agency can do

sales enablement, but they can also do some CFO work. They can do some strategy work. And that is what we mean by the full stack consultant. And the idea is that if you get very good at some new skills, which are not obvious to most people, like how to produce a really good, robust context library for your clients, you and the company can do amazing work. It can be done.

John Jantsch (05:15.385)

Mm-hmm.

Steve (05:41.166)

incredibly quickly and we’re learning more and more every day about what that looks like. So today, this morning, I did about, and this sounds ridiculous when you hear it from the outside and I understand that it sounds ridiculous, but I did about, in about two hours with 30 minutes of my work and an hour and half of just waiting around for the AI to finish its work, about 260 hours of design, interface work, copywriting.

and development. I don’t do any of those things in the past life. I have no skills in those things, but I know what to ask for. I know what I want and I know what good looks like and now I can get it. So it’s an amazing time that we live in.

John Jantsch (06:14.232)

Mm-hmm. Yeah.

John Jantsch (06:24.731)

I want to go back to a point you made there because, I have jokingly, but seriously said, you know, marketing is everything. And what I really meant by that was in a lot of small businesses, I would go into, there were a lot of things I had to fix that weren’t under the, you know, the heading of marketing a lot of times, because if marketing was going to work or we were going to grow the business, I had to get involved in this area over here. Sales was a typical one. Customer service is another one that, know, that you don’t always hire a marketing agency for.

But I would get into it out of necessity. And I think what you’re really pointing to is a great point, this idea of, you go into a business, it’s not just a matter of offering a suite of like, what do you need? It’s more like I can be more effective at doing my job that you hired me for if I can actually easily fix an area over here that I may not have true expertise in, or I couldn’t spend the time because I wasn’t being paid to fix their P &L, for example.

so I think that’s a great point. Let me back up again, because I I circled, I wanted the word context. that, let’s spend a little time talking about that. Cause I think AI has gotten better, but I also think prompters are getting better. and we’re realizing, you know, we get better output with, context. how do you give a, how, how in your view is probably a really long answer. How in your view, do you give AI the proper context?

Steve (07:52.408)

So when most people talk about context and there’s a term called context engineering, they’re mostly talking about it in the terms of like a single task that’s going on. What we mean by context engineering is how does the AI know everything about your business? that whenever you pull up a task to do that you actually, the AI can, it’s really hard to explain without getting into the weeds, but here’s my best shot.

John Jantsch (07:58.512)

Mm-hmm.

Steve (08:22.668)

So imagine that you have like the world’s best employee on every single task that could be done in your business, but they have amnesia. Every single time you give them a new task, they know nothing. So you have to train them. And that sounds like a really painful thing to have to do. But if you build a context library and only has to be done once to start, you can train that, you can give that AI like,

10 years of training in about 10 seconds. So it forgets all the time, but it learns like years in seconds. So all you gotta do, like this is how I boot up my instance of how I’m AI in my world as the CEO of our company. I onboarded the AI, I go look at the, I literally create an onboarding file. I say, go look at the onboarding file and get yourself onboarded. And 10 seconds later, it knows exactly like,

John Jantsch (08:54.629)

Mm-hmm.

Steve (09:20.418)

from a meta perspective, how we’re going to do our work today. And I’ll say, go look at that folder and let’s do this task, like redesign our interface for this page in our system. And knows exactly how I like to work. It knows exactly how I want design options. And as a marketer, you’ll appreciate this. you can go in and you’re doing, let’s say you’re doing ad variations. You go and ask for

You don’t even have to be that specific. If it knows everything about your business, you just say, give me five ad variations on this one topic or this one offer we’re making. Sends it back. You look at it. You’re like, like that one the most. And I’ve had the AI give me like the rationale for like, is scored it and ranked it. Then I could give me five more variations on that one. And then five more on that one. And one of the things that’s not obvious to people is that the cost of variations is almost zero.

John Jantsch (10:05.177)

Mm-hmm.

John Jantsch (10:10.768)

Right.

Steve (10:17.58)

So you can ask for an infinite number of variations of.

John Jantsch (10:17.594)

Yeah.

Yeah, I do that with subject lines for emails. mean, same thing. It’s like, kind of like the idea of this one. Iterate on that 10 more times. Yeah.

Steve (10:27.31)

Yeah, but you can do it for really big things too. So it’s not just like a single subject. You can do it for an entire interface, like an entire set of code. so like, because it works so fast and the cost of its work is so low, it transforms the way you approach the work. so customizing campaigns down to the individual level, not a problem anymore.

John Jantsch (10:31.193)

Yeah, yeah. Right.

Mm-hmm.

Steve (10:57.25)

Like I can find your LinkedIn profile, can scrape it and I can send you like an entire landing page that’s speaking directly to you. And it cost me a penny to do. And so there are things that we can do that were quite literally impossible before that now makes sense.

John Jantsch (11:16.543)

This might be good time to talk platforms and technologies a little bit. Are you agnostic or have you really gone all in and maybe it’s so complex that you can’t really say it in one sentence, but is like, are you a Gemini person? Are you a Chad’s EBT person or have you really building your own stuff?

Steve (11:36.942)

We’re definitely not building our own stuff. We have a very particular point of view, which is we’re serving companies and companies will eventually choose their LLM of choice. And that’s what they’re going to do all of their work on. So we are, we’re not hitching our wagon to any one LLM. We also have the point of view that for the most part, most AI rappers go away. So an organization is going to build their own software.

John Jantsch (12:01.679)

Yeah, yeah, yeah.

Steve (12:06.894)

So that’s our long-term bet. And so we’re just using whatever one is most productive. I personally have the max subscription on Claude, OpenAI and Gemini. I’m mostly using Claude right now because Claude Cowork and Claude Code just came out. And so if you listen to this like a month later, maybe I’m on something else by then, but Claude Cowork has been that tool alone.

John Jantsch (12:28.558)

You

Steve (12:33.548)

has transformed our operations in two weeks. Like we literally operate day to day differently now because of that tool. So, whatever one’s working the best when the next time we talk is the one we’ll be on then.

John Jantsch (12:36.346)

Yes.

John Jantsch (12:45.349)

Yeah.

Yeah. You know, I contended for a long time that just what you said, it’s, it’s going to be plumbing. It’s not going to be, Oh, I use this tool or that too. It’s going to be, no, this already works with what I use. And I really feel like, doesn’t that give Microsoft and Google because of their installed user base? mean, you know, I fire up Gmail and all of a sudden it’s like, Oh, there’s a new tool. Um, you know, I can opt into, you know, I mean, doesn’t that give them an advantage? And also I think the other thing, the first version of AI tools.

Is there better kind of use them by themselves? Well, now all of sudden we got collaboration built in, which I think was a big missing part. And so it’s like working the way people work already.

Steve (13:27.214)

Yeah, I think the like all other things being equal, Microsoft and Google have the biggest moat around it. However, for the longest time, Chad GPT was the best tool. And now Claude is by far the best tool. so I would have thought that if it was true that Microsoft and Google would be like for sure would win, it would have happened.

John Jantsch (13:34.372)

Mm-hmm.

John Jantsch (13:51.525)

Yeah, yeah, yeah, yeah.

Steve (13:52.224)

I know because they had not only they have the user base, they have all the documents and that’s, that’s what the AI needs for context. But as it turns out, the AI does not read and work with the file formats that we all produced over the last 20 years, which was PowerPoints and Word documents and all of those kinds of things. So there’s, there’s going to be a shift around that as well, which I think will loosen.

John Jantsch (14:08.995)

the

Steve (14:18.382)

the moat that they have because we’re not going to be stuck on PowerPoint anymore. Like I, the, in the last couple of weeks, I’ve been on this kick of, and I think this is just true. I will never use keynote or PowerPoint ever again. Um, and I’m not using like another AI tool. just build HTML documents and it does exactly what I want. And I, that’s my presentation style. Um, we do SOPs in our business. Everybody in our company builds HTML.

John Jantsch (14:32.155)

Mm.

Steve (14:46.132)

S O P S because you can just speak into a computer. HTML files open everywhere. And it’s also a good language for the LLMs to understand because it’s way easier to read than, than a PowerPoint. There’s others. If you pay attention to how software engineers are using AI, you’ll have a, you’ll have a glimpse of the future. They’re mostly using file formats that they’re comfortable with and that are, that work well for.

John Jantsch (14:57.147)

yeah.

Steve (15:15.182)

development, like markdown files and things like that. So that’s what you’ll see them suggest. Like you have to use markdown files for these things. And, what our point of view around this, and I think this will just prove to be true is that we need to be building like artifacts or deliverables, whatever you want to call it for humans and AI, not just humans. Like humans only is like PowerPoint, like LLMs hate PowerPoint. I hate word document.

John Jantsch (15:17.722)

Yeah, yeah, yeah.

John Jantsch (15:43.201)

can’t can’t can’t read them at all.

Steve (15:44.878)

There’s so much code around it, right? So then you have the like markdown files and things that most humans they look at it. Like I can’t, I can’t, a picture is worth a thousand words. It’s a real thing. Like we need to see visuals and workflows and all those things. And so HTML happens to do both of those incredibly well. So whether or not we’re right on that, I don’t know, but for now it’s like transforming the way that we do work because we can now.

build things that both our humans understand, the LLMs understand, and also there’s this magical thing that happens when a non-technical person speaks a website into existence, and just presses a button and it’s live. So it’s also a really good AI adoption tool, because it’s cool, right? Like it’s cool to like, you build something beautiful. So as a marketer, if you have a design system,

Most companies would never spend 30, 40, $50,000 on. You can speak one of those into existence. Like you can do it right now. Then everything that gets designed looks great in your company. And now everybody’s sharing beautifully designed. SOP documents. Like that’s, that’s a weird thing to think about, but it’s like, I like doing it. It looks nice. it explains what I explains my thoughts and my process. And so, yeah, I think, I think this year is going to be.

transformative in how we all do work and I don’t think it’s going to look the same by the end of the year.

John Jantsch (17:17.11)

So, and I know you have an answer for this, but this, I’m guessing listeners are out there going, okay, if I can just speak this stuff into existence, am I going to just start creating stuff without any kind of guardrails and without any human intervention? where’s the, you know, the pushback you’re getting from people that hate AI. So imagine the people that love AI, but don’t want to be embarrassed.

Steve (17:43.31)

What do you mean by guardrails specifically?

John Jantsch (17:46.123)

just, just meaning like, if I can design all these things, who’s going to actually go and make sure that they’re, they’re being done right. That they look good, that they say what they’re supposed to say. Cause you know, some of, particularly some of the image, you know, generates today. I mean, there’s, it’s just like appalling. Some of the things that show up in, in some of those.

Steve (18:06.478)

Well, I think there’s trying to figure out the 32nd way of answering this question. So the way we look at how work is done is by deliverables. you can look at it as a process, you can look at it as tasks, you can look at it as deliverables. But if you look at it as a deliverable, is that that’s when the thing ends. And that’s when the human has to look at it. It’s when the deliverable is done.

John Jantsch (18:18.864)

Right.

Steve (18:31.182)

First of all, should have the AI do a QC process on itself. You can do that. And it actually does a really good job of QCing its own work. So that’s the thing that most people don’t understand. But then once it comes off the press, whatever metaphor you want to use, and a human looks at it and says, are we sending this out? And if you treat it, and this is a language that most knowledge workers don’t like, it’s a factory now. And so you don’t QC every

energy drink can that comes off the line. But you look at some of them, right? And you know that if this one is this one’s off, well, we got to look at the ones that just went out the door because maybe they have a defect as well. So it becomes more of a factory mindset, knowing that if you if you have a good manufacturing process and that this again, like marketing agencies will hate this like, but that is that it but

John Jantsch (19:02.97)

Right.

John Jantsch (19:22.297)

Yeah. Yeah. Even the word factory there, they’re going to cringe at. Right.

Steve (19:26.894)

Like if you do not turn your marketing agency into a factory in 2026, you will be out of business. Like let’s go have a, we’ll do it next year and we’ll see whether or not that’s true. Like you have to, you’ll have to learn good workflows. You need to learn good work instructions. You need to learn good QC process. And so, and once you do, you can start mass producing things that are top notch and

John Jantsch (19:37.403)

Yeah.

Steve (19:56.138)

knowledge work will be turned into a factory. And then what gets layered on top of that is a new skill set, which is not 100 % clear what that is yet, but we will invent new things to do that will just add value on top of that.

John Jantsch (20:14.085)

Fascinating, Steve. Appreciate you stopping by the Duct Tape Marketing Podcast. Where do you want to invite people to find out more about, I think it’s simpleconsultants.ai and obviously about your book?

Steve (20:26.978)

Yeah, well, if you’re up for it, I would love to give everybody in your audience free access to our BlackBelt training. We’ll create a page specifically for your network. It’ll be roiassociation.ai.

John Jantsch (20:47.931)

Awesome. And we’ll put that in the show notes as well. So that was ROI.association, is that what you said?

Steve (20:54.824)

roiassociation.ai.

John Jantsch (20:56.973)

dot, dot A. Okay. Got it. Awesome. Well, as I said, we’ll put that in the show notes as well. So Steve, again, appreciate you stopping by. This is awesome. And hopefully we’ll run into you one of these days out there on the road.

Steve (21:11.662)

Absolutely. Thanks, John.

John Jantsch (00:01.218)

Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch. My guest today is Kyle Austin Young. He’s an award winning strategy consultant, speaker and writer who helps leaders, entrepreneurs and high achievers accomplish big, meaningful goals. His work centers on a unique decision-making and goal achievement framework that he calls probability hacking, a method designed to analyze and intentionally improve the odds of success in any pursuit. We’re going to talk about his newest book.

Success is a numbers game. Achieve bigger goals by changing the odds. So Kyle, welcome to the show.

Kyle Austin Young (00:37.348)

Thank you for having me. Honored to be here.

John Jantsch (00:39.278)

So I’m going to start with the premise that I’m sure you, I won’t be the first person to ask this question. I think a lot of times when people talk about goals, they think about hustle or mindset or heck even luck. You are saying it’s more about odds. What’s different in that shift?

Kyle Austin Young (00:59.15)

Yeah, let me give you sort of an example. Let’s say that we’ve set the goal of training to run a marathon. Let’s say that’s something that we’ve decided we want to accomplish and we hire a running coach and she says, I can get you ready in time, but you’re gonna have to do three things. I need you to eat, sleep, and train according to some specific regimens that I’m gonna create for you.

John Jantsch (01:02.872)

me

John Jantsch (01:14.829)

Mm-hmm.

Kyle Austin Young (01:16.334)

So let’s say that we know that one of these prerequisites is we’re to have to train according to some certain parameters. And so we identify some of the things that could go wrong, some of the things that might happen instead of what we want. And maybe we identify bad weather as something that could derail a training regimen. I’m currently preparing for a big wintery snowstorm. Let’s say that we identify injury as a potential risk, or maybe we identify that our kids might have a crisis that could overwhelm our schedule. So the question that I like to ask people is,

tell me how wanting to run a marathon is an antidote to any of those threats to our success. How does wanting to run a marathon change the weather? How does wanting to run a marathon prevent injury? How does wanting to run a marathon keep a crisis from happening in our kids’ lives? Certainly, we’re going to need a measure of commitment and hustle in order to be successful. But ultimately, what we’re going to really need is we need some creative solutions to the things that could keep us from getting what we want.

So I believe that we can understand probabilities similar to the way we’ve traditionally understood matter. It can’t be created or destroyed, but it can be transferred and rearranged. The odds of success, the odds that we want for our goal are currently hiding in our potential bad outcomes. When we identify what those things are and what we can do about them, we can tilt the odds in our favor.

John Jantsch (02:30.488)

So it’s all about quantum physics. Is that what you’re saying? So when you talk about moving matter around, was the first thought I had. Sure.

Kyle Austin Young (02:33.54)

Very little physics in the book. I don’t think I’ve ever taken a physics class.

Kyle Austin Young (02:40.418)

Well, I do think that there’s a lot of truth in the idea that a lot of people want to conjure good odds out of thin air. This idea that maybe I can wish myself into a better position. And I don’t think that’s true. I think that a lot of times when we’re pursuing a goal, we’re encouraged to think positive. Don’t worry about what could go wrong. If it’s meant to happen, it’ll happen. Just focus on the positive. I encourage people to do the exact opposite. I tell people to think negative. I tell people, for everything that has to go right in order for you to get what you want, identify the potential bad outcomes. Identify the things that could happen instead of what you want.

John Jantsch (02:55.8)

Thank

Kyle Austin Young (03:09.464)

and use your creativity to systematically de-risk your goals.

John Jantsch (03:13.826)

So in your bio, and I know in the book itself, you talk a lot about probability hacking. So let’s talk about what that is or how you define

Kyle Austin Young (03:22.916)

Yeah, I define probability hacking as doing exactly what we just did. It starts with getting an idea of what’s going to have to go right and then identifying what could go wrong and then looking for creative solutions. I’ll tell a different example. You know, when I first graduated from college, I wasn’t excited about the entry level positions that I was seeing. I wanted to try for something more ambitious. So I actually applied to become the product development director at a growing health organization. I was 21 years old. If hired, I was going to be managing people in their 50s, 60s, 70s, people with PhDs and master’s degrees.

a crazy thing to do, but I got an interview and I wanted to make the most of it. So even at that time, I did what I essentially do now for a living. I created what I call a success diagram. I only needed to get a job offer at that point. That was the only step left, but I looked at what are the potential bad outcomes that could happen instead of me getting that job offer. And so I identified three. And so I’m giving this example. You kind of had the quantum physics concern because there’s no numbers here. I’m just going to show you how we can do this at a story level. One of the risks I identified was they might not hire me because of how young I looked.

John Jantsch (04:15.054)

Bye.

Kyle Austin Young (04:21.54)

I might walk in and they take one look and say, he can’t lead this team. So one of the very practical things I did to combat that is I just grew a beard. I still have the beard today. It was something that made me look about 10 years older than I was. And I knew that if I could do that, it would maybe take the edge off of that concern a little bit. A second bad outcome that I identified, a potential bad outcome rather, was there might be concerns over my lack of experience, which were valid. I didn’t have a deep resume. I had just graduated from college. So what I did was I couldn’t lie. I wasn’t going to

John Jantsch (04:22.126)

Right.

Kyle Austin Young (04:49.54)

pretend that I had experience I didn’t have, but I wanted to show the quality of my thinking. So I actually typed up a plan for how I was going to turn this department around. It was so thick, I had to have it spiral bound. It was a book. And every person I went to and interviewed with, I gave them a copy of it. And the goal was when they would ask me questions about my past, I would just redirect it to be a conversation about the future. What experience do you have with whatever the case might be, product development? Great question. Here’s my plan for product development. Let’s talk about the vision that I have for this role if I’m given the opportunity.

The third potential bad outcome I identified was maybe they would be concerned that I couldn’t really get along with the existing team because there was just such a big generational gap. So I used a strategy that I’m still using today. It’s worked really well for me. I asked one of the people in the organization if the product development team had read any books recently as a group. She listed a few titles, I think it was three or four, and I went out and read every single one of them. And what that did is it gave me the ability to have conversations with the team that no other applicant could have. I understood their goals, I understood their jargon, I could make inside jokes.

John Jantsch (05:25.538)

Mm-hmm.

Kyle Austin Young (05:48.56)

There was a group interview where it was me and a bunch of people 20, 30 years older than me with a lot more experience trying to decide who was going to ultimately win the opportunity to lead this department. And one of the books that they read was called The Wuffy Factor. I don’t know if you remember that. was a book about how to, you remember the Wuffy? It was about how brands are in social capital. This was close to 15 years ago. And I remember being in that interview and I said, you know, I think this idea that we’re discussing could help us get a lot of Wuffy.

John Jantsch (05:57.934)

Right.

I remember saying that, yeah, yeah.

Kyle Austin Young (06:11.632)

And I remember looking around and these other applicants, their eyes are bugging out of their heads. What on earth did he just say? You know, is he feeling, okay, what does he mean? We’re going to get a lot of wealthy out of this. But the existing team members, they were all laughing and nodding along. They knew exactly what I was talking about. We were reading the same books. So when all was said and done, I got that job. At 21 years old, I became the product development director for a health organization. It dramatically accelerated my career, but it started with this idea of probability hacking. It started with getting clear on what I wanted and getting clear on what was going to have to go right. Then thinking negatively,

identifying the risks to my success and not resorting to desire as an antidote to uncertainty, but instead using my creativity to solve those problems.

John Jantsch (06:49.006)

So you gave very specific details and steps of what you did, but it sounded, it started to sound a bit like a framework, which I know you have in the book. So were those steps that you gave me a part of that framework? Do you want to outline what that framework is?

Kyle Austin Young (07:04.41)

Sure, I encourage people to start by creating what I call a success diagram. A success diagram is you write down what’s the goal, what do I want to accomplish? I do that at the top right of the page. And then to the left, I just try to list out everything that’s gonna have to go right in order for me to get what I want. So it might be run a marathon. And what I call critical points, the prerequisites to my success are eat according to the regimen my coach gives me, sleep according to the regimen she gives me, train according to the regimen she gives me. So now I have the path, I have the destination.

And then for each one of those things that has to go right, I try to identify the potential bad outcomes. These aren’t just things that could go wrong, they’re alternate outcomes to success. Things that would be so significant they would completely derail the goal if any of them were to come true. After I have those mapped out, I try to just assign a level of risk to each of them. Is this a low risk potential bad outcome, a medium risk, a high risk, so they know how to prioritize? And then probability hacking again is using our creativity to try to find solutions to that. If I’m concerned about

you know, inclement weather derailing my training routine, I might need a treadmill indoors or need to find some alternate exercises that can allow me to build my fitness on days when I can’t go for a run. If I’m concerned about scheduling issues, something happening at my kid’s school, then I might want to train first thing in the morning or I might want to buy an extra pair of running shoes to keep in the car so that I can train at a park if I need to, if my day gets derailed.

John Jantsch (08:20.034)

In a lot of ways, what I’m hearing you describe is, I mean, think there are a lot of people that have mapped out the plan to run the marathon. mean, you can buy books, entire books, will tell you exactly what to do on day one, day two. But what you’re saying a lot of people miss is integrating the whole, you know, of life. And I think in a lot of ways, you’re really just asking people to step back and you’re calling it what could go wrong. But what you’re really doing is saying, hey, you have to have a grasp of reality.

Kyle Austin Young (08:31.29)

Sure.

Kyle Austin Young (08:49.764)

I think you do have to have a grasp of reality. I think that when we consider these statistics that are floating around all the time, just how many people fail at their New Year’s resolutions, how this vast majority of mergers and acquisitions fail to create lasting value for shareholders, how many new businesses will ultimately fail in the first few years after their existence, we start to recognize that it’s because we haven’t stopped to consider the things that could go wrong. And I’ll demonstrate that with just a little bit of numbers. Let’s use that marathon example. There’s three things that have to go right. I need to eat, sleep, and train according to a certain regimen.

John Jantsch (08:51.307)

me

John Jantsch (08:57.139)

Mm-hmm. Right.

John Jantsch (09:13.763)

Mm-hmm.

Kyle Austin Young (09:19.14)

Well, let’s take some imaginary numbers and try to estimate how likely we are to accomplish each of those three things. Maybe we think it’s 70 % across the board. 70 % chance I’ll stick with the diet, 70 % chance I’ll sleep the way I’m supposed to, 70 % chance I’ll train the way I’m supposed to. What a lot of people do is they fall into a trap called averaging. If they feel good about the individual prerequisites, they feel good about the goal as a whole. That’s not actually logically sound, it’s not mathematically sound. What we have to do is multiply those numbers together to find our overall odds of success.

John Jantsch (09:45.261)

Yes.

Kyle Austin Young (09:47.204)

And if we do that, we find that even though we feel really good about each of these things, 70 % across the board, our overall odds of being ready on race day are only 34%. And that I believe explains a lot of the dysfunction in our world. Why are people failing at goals and wondering, how did this not go the way that I expected it to? I felt good about each individual step. Well, you averaged in your head. You didn’t take the time to understand what your overall odds were. And because of that, maybe you didn’t pay as much attention to your opportunity to change your odds as you could have. Maybe you didn’t get that grasp on reality exactly like what you said.

John Jantsch (10:14.926)

Thank

Kyle Austin Young (10:16.27)

and try to the odds in your favor.

John Jantsch (10:18.766)

Is there any, do you ever run the risk or do you find that people might, like if I sat down thought, oh, my odds of actually being prepared on race day is only in the 30 % range, is there any chance that I say, why bother?

Kyle Austin Young (10:32.538)

There could be, but if we’re taking the time to think negative and identify the bad outcomes that are dragging those odds down, then we can use our creativity and see if we can’t change those numbers, at least in how we understand them, to look like something that’s more optimistic. You if we are using our creativity to address the risk of bad weather when we need to train, or address the risk of injury, or address the risk of our schedule being sabotaged, then we can ultimately run the numbers again. And maybe by the time we’re done optimizing this plan,

John Jantsch (10:33.902)

Yeah

Kyle Austin Young (10:59.812)

we end up feeling like it’s 90 % across the board. That’s still not a 90 % chance of success, but I believe it’s in the 70s. It’s a lot better.

John Jantsch (11:05.166)

Yeah. So, so do you find that you have to help people reframe this idea of failure even?

Kyle Austin Young (11:14.426)

Give me an example of what you mean by that.

John Jantsch (11:16.844)

Well, I mean, in some ways you’re, as I listened to you talk about the steps, you’re, you’re, you’re not saying that’s failures of possibility, but that it’s part of the equation. and a lot of people, you know, would have, I think some people would, would struggle with that idea. I, I’m not saying what you’re talking about doesn’t make sense, but just the mindset that a lot of people have that might be hard to overcome.

Kyle Austin Young (11:41.37)

Sure.

Absolutely. Failure is going to be part of the equation. One of the things that I encourage people to consider in the book is the power of multiple attempts. If you’re chasing a goal that’s really unlikely, often one of the most reliable ways to ultimately succeed is to try more than one time. I tell the story of the miracle on ice in the first chapter of the book. I got to interview Jack O’Callaghan who played on that 1980 hockey team that beat the Soviet Union. And a lot of people consider that a miracle. It’s been called the greatest sporting event of the 20th century, I believe, by Sports Illustrated.

John Jantsch (11:57.518)

Right.

Kyle Austin Young (12:14.028)

And as an individual event, it was really miraculous. But when you recognize that over the course of this Olympic rivalry, the United States played the Soviets nine times and won two, that’s not that remarkable. Winning two times out of nine isn’t unheard of. So was it surprising that they won the game they won? Sure. But the odds told us that we would expect them to win some games. And that’s ultimately what they did. And what’s interesting is when I interviewed Jack, he told me that in the locker room before they went out to take the ice for that game,

John Jantsch (12:23.842)

Mm-hmm. Right.

John Jantsch (12:35.18)

Yeah.

Kyle Austin Young (12:42.244)

Coach Herb Brooks gives this speech and there’s a movie about it and the movie has some quotes that are really powerful. What Jack told me is he said he doesn’t remember the exact words that were spoken. But he says he remembers that when he left the locker room, they’re trudging down to take the ice. He says he remembers leaving with the idea that his coach believed if we played them 10 times, they might beat us nine times, but they’re not going to beat us tonight. And so there was an expectation that failure was going to be a part of that, but they had an opportunity for tonight to be the exception. And ultimately it was.

John Jantsch (13:10.446)

I remember vividly watching that in my dorm room in college. does this, like a marathon I would call a long-term goal, particularly for somebody who hasn’t run one, right? They should start early, right? Can this be applied to short-term decisions as well?

Kyle Austin Young (13:14.956)

Amazing. I missed it by a few years, but I’m jealous.

Kyle Austin Young (13:24.666)

Sure. Sure.

Kyle Austin Young (13:33.166)

absolutely. You know, in the context of me trying to get that job, I just did this as I headed into an interview. It was going to all take place in a day. When we have something that needs to go right, one of the best things we can do to help it go right is think about what could go wrong. Ultimately, that’s what’s dragging our probability down. If you think about flipping a coin, let’s say you need it to land on heads, you have a 50 % chance of success. Why? Why don’t you have a 100 % chance of success? Well, because it might land on tails, and there’s a 50 % chance of that happening. Now, I don’t know how to rig a coin to make it…

do what I want it to do. But in life, a lot of times we can rig it or we can re-rig it in our favor. We can try to take the risk out of the bad outcomes, bring those odds over to our side.

John Jantsch (14:11.448)

So if somebody hasn’t thought this way, what’s kind some of the first things you try to help people? And again, I don’t know if you actually consult on this or teach courses on this as well, but what are some of the first things you try to do to get people to start putting this way of thinking? Because I think a lot of times these things are just mindset. So what do you get them to start thinking this way? What are some of the first things?

Kyle Austin Young (14:32.784)

Well, in the book, I tell people that I think there are four paths to success. One of them is some people just get lucky. I tell the story of Norma Jean Doherty. She’s working at an aviation munitions factory in the war, and a photographer comes to take pictures for a military magazine to inspire the troops. He notices Norma Jean, thinks she’s really beautiful, says, can I take some pictures for you for magazines that don’t have anything to do with the military? And she said, sure. She ultimately finds a lot of success as a model and then goes on to star as an actress under the name Marilyn Monroe, has just this enormously successful career.

That is certainly a success story. Is it a success story we should reverse engineer though? If I meet a young woman who’s coming to me for training or coaching rather, can you tell me what I can do to become a successful Hollywood star? Would I say, well, the first thing you need to do is get a job at an aviation munitions factory and hope that someday a military photographer stops by and notices how pretty you are and says, can I take some pictures of you? No, that probably wouldn’t be a very reliable path to success. So some people succeed through luck. They succeed even though the odds are bad, simply because we expect unlikely events to happen sometimes.

Some people succeed, they don’t beat the odds, but they play them. We think about entrepreneurs, there are some really famous examples of people who heard that nine out of 10 businesses fail, and that was actually what inspired them to start 10 businesses or 15 businesses, was the belief that they were going to experience those predicted failures, but they would also experience the predicted successes. Some people succeed because they have advantages, they have areas of tremendous strength in their lives, and so they try to lean into those goals.

John Jantsch (15:41.314)

you

Kyle Austin Young (15:54.084)

That can often be something that’s really wise for us is asking the question, what are some goals that are pretty high probability goals for me right now that might bring bigger accomplishments within reach? One of the goals that I had for years was ultimately getting a book deal and hopefully getting a big advance and being able to publish that to a mass audience with a major publisher. At the time when I set that goal, it wasn’t really realistic for me, but I was able to pursue smaller goals that changed my odds. One of them was writing for major publications.

John Jantsch (16:01.42)

Mm-hmm.

Kyle Austin Young (16:21.04)

As you mentioned, I’ve written for sites like HBR, Fast Company, Psychology Today. But one of my favorite things and one of the reasons I was so excited to have the opportunity to come on is it’s an exciting full circle moment for me. When I first decided that I was going to try to write for some of these respected publications, get my voice out there and ultimately position myself for things like a book deal, the first site that took me was the Duct Tape Marketing Blog. It was in 2015. I remember I was in my grandmother’s house at the time. They were having a garage sale. I was helping out when I got the response. I couldn’t even tell you where I was sitting.

John Jantsch (16:31.63)

You

John Jantsch (16:42.292)

the

Kyle Austin Young (16:49.742)

and it was such an exciting thing. So it’s an honor to be with you here today. So that’s the third path of success is people making the most of areas where they have good odds. The fourth path is probability hacking, doing everything you can to tilt the odds in your favor.

John Jantsch (16:50.286)

you

John Jantsch (17:01.006)

So, you know, I was going to ask you about resilience. And then you kind of threw in that story about the entrepreneurs starting 10 businesses, but what, what connection do you think with the framework and just the whole mindset of resilience? What does it play?

Kyle Austin Young (17:17.774)

Well, it’s incredibly important if you’re going to especially be pursuing the path of repeated attempts. In the book, I tell the story of Thomas Edison. He’s in a race to try to get valuable patents surrounding the incandescent lamp. If he can get them, it’ll be something that’s transformational for his career. And what this race came down to is he and these other people were all trying to find a practical filament. They needed something that could glow hot enough to emit light without catching on fire and without snuffing out really quickly to the point where it wasn’t worth it. What Edison did that was different than these other people…

John Jantsch (17:23.0)

Yeah.

John Jantsch (17:29.709)

Mm-hmm.

Kyle Austin Young (17:47.376)

is he actually experimented with 6,000 different plant materials to find the one that worked best. He didn’t try to divine the right answer. He didn’t try to guess the right answer. The answer turned out to be, in his context, carbonized bamboo. And I don’t know about you. That would not have been my first guess. If you said, what are we going to use as a filament? I would have said, I bet it’s carbonized bamboo. That’s not where I would have started. It’s not where he started either. It took 6,000 attempts. But ultimately, he had a clear definition of success. He had a stopwatch, so to speak. And he was able to run more experiments than anyone else. And because of that,

John Jantsch (17:54.144)

Mm-hmm.

John Jantsch (18:04.718)

the

Kyle Austin Young (18:15.364)

he found these unlikely answers. so resilience is a big part of that. Some of it comes from, we need to be confident that there is going to be a best answer out there. And in his case, it wasn’t, you know, it was comparative. He could be confident that one option out of the 6,000 would be the best out of the 6,000. And he liked his chance of creating a great product with a wider net when it came to ultimately trying to find the best filament than he did with somebody who’s only trying two or three things.

John Jantsch (18:27.982)

Thanks.

John Jantsch (18:41.526)

Yeah, and there’s obviously, I don’t know that it’s all true, but you hear these stories that people would ask him, gosh, aren’t you tired of failing so much? He said, no, I just have one more thing out of the way that I know is not the answer.

Kyle Austin Young (18:55.116)

He has a quote attributed to him that’s, to have a great idea, have a lot of them. And I think it’s that exact same mentality. It’s not about being the smartest person in the room necessarily. A lot of times it’s being the most generative. It’s being the person who’s the most prolific and who ultimately uncovers that unlikely good idea.

John Jantsch (18:58.936)

Yeah, yeah. Yeah.

John Jantsch (19:12.396)

Yeah. And, and, you know, there’s, there’s certainly a mentality out there. People want to, you know, take the easy path, get rich quick, you know, be famous, all the things that, people aspire to. And I don’t, you know, the, people that really get there, you know, they just show up and do the work every day for a long time. Sometimes.

Kyle Austin Young (19:29.614)

Well, it’s one of the dangers of reverse engineering, like I mentioned, you know, the Marilyn Monroe story, we kind of chuckle at that, but I think we’re doing similar things in our daily lives. We’ll find somebody who started a successful organization and turns out he drives a blue convertible. So I should buy a blue convertible because clearly that’s got to be playing a role in his success. What if he just got lucky? I’m not saying that they did, but we need to be really careful about what we reverse engineer because just because someone is seeing good results doesn’t mean that they got there through good decisions.

John Jantsch (19:31.874)

Yeah, yeah.

Right? Yeah.

John Jantsch (19:46.924)

Yeah.

John Jantsch (19:54.646)

Yeah. Well, and I think a lot of times we miss the 10 years before, before they blew up, right? Yeah, exactly. Well, Kyle, I appreciate you stopping by the Duct Tape Marketing Podcast. Is there someplace you’d invite people to find out more about your work and to perhaps pick up success is a numbers game.

Kyle Austin Young (19:58.778)

Sure, yeah, that kind of quote that most overnight successes are 20 years in the making, sure.

Kyle Austin Young (20:14.0)

You can get a copy of the book pretty much anywhere, Amazon, Barnes & Noble, directly on the Penguin Random House website. Be honored if you did that. If you want to connect with me personally, I think we’ll probably put my website in the show notes, just kyleaustinyoung.com. But what I’d prefer you do, honestly, this was something that was just kind of an unexpected blessing of this journey, is I heard someone who was encouraging people to find them on LinkedIn, and I thought, that’s a strange thing to do. I’ll throw that idea out too. And that was many interviews ago, but it’s turned into one of just the best parts of this, is pretty much every day I wake up and someone has

John Jantsch (20:25.134)

Mm-hmm.

Kyle Austin Young (20:43.118)

sent me a message saying, I heard you here, I heard you there, can I ask you a question? It’s led to some really engaging conversations that I’ve really enjoyed, some fun opportunities for collaboration for me. So feel free to find me, Kyle Austin Young on LinkedIn. I’d love to hear from you.

John Jantsch (20:45.1)

Okay.

John Jantsch (20:56.618)

Awesome. Well, again, appreciate you stopping by and hopefully we’ll maybe we’ll run into one of these days out there on the road.

Kyle Austin Young (21:02.16)

That’d be great. Thanks.

John Jantsch (00:01.218)

Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch. My guest today is Kyle Austin Young. He’s an award winning strategy consultant, speaker and writer who helps leaders, entrepreneurs and high achievers accomplish big, meaningful goals. His work centers on a unique decision-making and goal achievement framework that he calls probability hacking, a method designed to analyze and intentionally improve the odds of success in any pursuit. We’re going to talk about his newest book.

Success is a numbers game. Achieve bigger goals by changing the odds. So Kyle, welcome to the show.

Kyle Austin Young (00:37.348)

Thank you for having me. Honored to be here.

John Jantsch (00:39.278)

So I’m going to start with the premise that I’m sure you, I won’t be the first person to ask this question. I think a lot of times when people talk about goals, they think about hustle or mindset or heck even luck. You are saying it’s more about odds. What’s different in that shift?

Kyle Austin Young (00:59.15)

Yeah, let me give you sort of an example. Let’s say that we’ve set the goal of training to run a marathon. Let’s say that’s something that we’ve decided we want to accomplish and we hire a running coach and she says, I can get you ready in time, but you’re gonna have to do three things. I need you to eat, sleep, and train according to some specific regimens that I’m gonna create for you.

John Jantsch (01:02.872)

me

John Jantsch (01:14.829)

Mm-hmm.

Kyle Austin Young (01:16.334)

So let’s say that we know that one of these prerequisites is we’re to have to train according to some certain parameters. And so we identify some of the things that could go wrong, some of the things that might happen instead of what we want. And maybe we identify bad weather as something that could derail a training regimen. I’m currently preparing for a big wintery snowstorm. Let’s say that we identify injury as a potential risk, or maybe we identify that our kids might have a crisis that could overwhelm our schedule. So the question that I like to ask people is,

tell me how wanting to run a marathon is an antidote to any of those threats to our success. How does wanting to run a marathon change the weather? How does wanting to run a marathon prevent injury? How does wanting to run a marathon keep a crisis from happening in our kids’ lives? Certainly, we’re going to need a measure of commitment and hustle in order to be successful. But ultimately, what we’re going to really need is we need some creative solutions to the things that could keep us from getting what we want.

So I believe that we can understand probabilities similar to the way we’ve traditionally understood matter. It can’t be created or destroyed, but it can be transferred and rearranged. The odds of success, the odds that we want for our goal are currently hiding in our potential bad outcomes. When we identify what those things are and what we can do about them, we can tilt the odds in our favor.

John Jantsch (02:30.488)

So it’s all about quantum physics. Is that what you’re saying? So when you talk about moving matter around, was the first thought I had. Sure.

Kyle Austin Young (02:33.54)

Very little physics in the book. I don’t think I’ve ever taken a physics class.

Kyle Austin Young (02:40.418)

Well, I do think that there’s a lot of truth in the idea that a lot of people want to conjure good odds out of thin air. This idea that maybe I can wish myself into a better position. And I don’t think that’s true. I think that a lot of times when we’re pursuing a goal, we’re encouraged to think positive. Don’t worry about what could go wrong. If it’s meant to happen, it’ll happen. Just focus on the positive. I encourage people to do the exact opposite. I tell people to think negative. I tell people, for everything that has to go right in order for you to get what you want, identify the potential bad outcomes. Identify the things that could happen instead of what you want.

John Jantsch (02:55.8)

Thank

Kyle Austin Young (03:09.464)

and use your creativity to systematically de-risk your goals.

John Jantsch (03:13.826)

So in your bio, and I know in the book itself, you talk a lot about probability hacking. So let’s talk about what that is or how you define

Kyle Austin Young (03:22.916)

Yeah, I define probability hacking as doing exactly what we just did. It starts with getting an idea of what’s going to have to go right and then identifying what could go wrong and then looking for creative solutions. I’ll tell a different example. You know, when I first graduated from college, I wasn’t excited about the entry level positions that I was seeing. I wanted to try for something more ambitious. So I actually applied to become the product development director at a growing health organization. I was 21 years old. If hired, I was going to be managing people in their 50s, 60s, 70s, people with PhDs and master’s degrees.

a crazy thing to do, but I got an interview and I wanted to make the most of it. So even at that time, I did what I essentially do now for a living. I created what I call a success diagram. I only needed to get a job offer at that point. That was the only step left, but I looked at what are the potential bad outcomes that could happen instead of me getting that job offer. And so I identified three. And so I’m giving this example. You kind of had the quantum physics concern because there’s no numbers here. I’m just going to show you how we can do this at a story level. One of the risks I identified was they might not hire me because of how young I looked.

John Jantsch (04:15.054)

Bye.

Kyle Austin Young (04:21.54)

I might walk in and they take one look and say, he can’t lead this team. So one of the very practical things I did to combat that is I just grew a beard. I still have the beard today. It was something that made me look about 10 years older than I was. And I knew that if I could do that, it would maybe take the edge off of that concern a little bit. A second bad outcome that I identified, a potential bad outcome rather, was there might be concerns over my lack of experience, which were valid. I didn’t have a deep resume. I had just graduated from college. So what I did was I couldn’t lie. I wasn’t going to

John Jantsch (04:22.126)

Right.

Kyle Austin Young (04:49.54)

pretend that I had experience I didn’t have, but I wanted to show the quality of my thinking. So I actually typed up a plan for how I was going to turn this department around. It was so thick, I had to have it spiral bound. It was a book. And every person I went to and interviewed with, I gave them a copy of it. And the goal was when they would ask me questions about my past, I would just redirect it to be a conversation about the future. What experience do you have with whatever the case might be, product development? Great question. Here’s my plan for product development. Let’s talk about the vision that I have for this role if I’m given the opportunity.

The third potential bad outcome I identified was maybe they would be concerned that I couldn’t really get along with the existing team because there was just such a big generational gap. So I used a strategy that I’m still using today. It’s worked really well for me. I asked one of the people in the organization if the product development team had read any books recently as a group. She listed a few titles, I think it was three or four, and I went out and read every single one of them. And what that did is it gave me the ability to have conversations with the team that no other applicant could have. I understood their goals, I understood their jargon, I could make inside jokes.

John Jantsch (05:25.538)

Mm-hmm.

Kyle Austin Young (05:48.56)

There was a group interview where it was me and a bunch of people 20, 30 years older than me with a lot more experience trying to decide who was going to ultimately win the opportunity to lead this department. And one of the books that they read was called The Wuffy Factor. I don’t know if you remember that. was a book about how to, you remember the Wuffy? It was about how brands are in social capital. This was close to 15 years ago. And I remember being in that interview and I said, you know, I think this idea that we’re discussing could help us get a lot of Wuffy.

John Jantsch (05:57.934)

Right.

I remember saying that, yeah, yeah.

Kyle Austin Young (06:11.632)

And I remember looking around and these other applicants, their eyes are bugging out of their heads. What on earth did he just say? You know, is he feeling, okay, what does he mean? We’re going to get a lot of wealthy out of this. But the existing team members, they were all laughing and nodding along. They knew exactly what I was talking about. We were reading the same books. So when all was said and done, I got that job. At 21 years old, I became the product development director for a health organization. It dramatically accelerated my career, but it started with this idea of probability hacking. It started with getting clear on what I wanted and getting clear on what was going to have to go right. Then thinking negatively,

identifying the risks to my success and not resorting to desire as an antidote to uncertainty, but instead using my creativity to solve those problems.

John Jantsch (06:49.006)

So you gave very specific details and steps of what you did, but it sounded, it started to sound a bit like a framework, which I know you have in the book. So were those steps that you gave me a part of that framework? Do you want to outline what that framework is?

Kyle Austin Young (07:04.41)

Sure, I encourage people to start by creating what I call a success diagram. A success diagram is you write down what’s the goal, what do I want to accomplish? I do that at the top right of the page. And then to the left, I just try to list out everything that’s gonna have to go right in order for me to get what I want. So it might be run a marathon. And what I call critical points, the prerequisites to my success are eat according to the regimen my coach gives me, sleep according to the regimen she gives me, train according to the regimen she gives me. So now I have the path, I have the destination.

And then for each one of those things that has to go right, I try to identify the potential bad outcomes. These aren’t just things that could go wrong, they’re alternate outcomes to success. Things that would be so significant they would completely derail the goal if any of them were to come true. After I have those mapped out, I try to just assign a level of risk to each of them. Is this a low risk potential bad outcome, a medium risk, a high risk, so they know how to prioritize? And then probability hacking again is using our creativity to try to find solutions to that. If I’m concerned about

you know, inclement weather derailing my training routine, I might need a treadmill indoors or need to find some alternate exercises that can allow me to build my fitness on days when I can’t go for a run. If I’m concerned about scheduling issues, something happening at my kid’s school, then I might want to train first thing in the morning or I might want to buy an extra pair of running shoes to keep in the car so that I can train at a park if I need to, if my day gets derailed.

John Jantsch (08:20.034)

In a lot of ways, what I’m hearing you describe is, I mean, think there are a lot of people that have mapped out the plan to run the marathon. mean, you can buy books, entire books, will tell you exactly what to do on day one, day two. But what you’re saying a lot of people miss is integrating the whole, you know, of life. And I think in a lot of ways, you’re really just asking people to step back and you’re calling it what could go wrong. But what you’re really doing is saying, hey, you have to have a grasp of reality.

Kyle Austin Young (08:31.29)

Sure.

Kyle Austin Young (08:49.764)

I think you do have to have a grasp of reality. I think that when we consider these statistics that are floating around all the time, just how many people fail at their New Year’s resolutions, how this vast majority of mergers and acquisitions fail to create lasting value for shareholders, how many new businesses will ultimately fail in the first few years after their existence, we start to recognize that it’s because we haven’t stopped to consider the things that could go wrong. And I’ll demonstrate that with just a little bit of numbers. Let’s use that marathon example. There’s three things that have to go right. I need to eat, sleep, and train according to a certain regimen.

John Jantsch (08:51.307)

me

John Jantsch (08:57.139)

Mm-hmm. Right.

John Jantsch (09:13.763)

Mm-hmm.

Kyle Austin Young (09:19.14)

Well, let’s take some imaginary numbers and try to estimate how likely we are to accomplish each of those three things. Maybe we think it’s 70 % across the board. 70 % chance I’ll stick with the diet, 70 % chance I’ll sleep the way I’m supposed to, 70 % chance I’ll train the way I’m supposed to. What a lot of people do is they fall into a trap called averaging. If they feel good about the individual prerequisites, they feel good about the goal as a whole. That’s not actually logically sound, it’s not mathematically sound. What we have to do is multiply those numbers together to find our overall odds of success.

John Jantsch (09:45.261)

Yes.

Kyle Austin Young (09:47.204)

And if we do that, we find that even though we feel really good about each of these things, 70 % across the board, our overall odds of being ready on race day are only 34%. And that I believe explains a lot of the dysfunction in our world. Why are people failing at goals and wondering, how did this not go the way that I expected it to? I felt good about each individual step. Well, you averaged in your head. You didn’t take the time to understand what your overall odds were. And because of that, maybe you didn’t pay as much attention to your opportunity to change your odds as you could have. Maybe you didn’t get that grasp on reality exactly like what you said.

John Jantsch (10:14.926)

Thank

Kyle Austin Young (10:16.27)

and try to the odds in your favor.

John Jantsch (10:18.766)

Is there any, do you ever run the risk or do you find that people might, like if I sat down thought, oh, my odds of actually being prepared on race day is only in the 30 % range, is there any chance that I say, why bother?

Kyle Austin Young (10:32.538)

There could be, but if we’re taking the time to think negative and identify the bad outcomes that are dragging those odds down, then we can use our creativity and see if we can’t change those numbers, at least in how we understand them, to look like something that’s more optimistic. You if we are using our creativity to address the risk of bad weather when we need to train, or address the risk of injury, or address the risk of our schedule being sabotaged, then we can ultimately run the numbers again. And maybe by the time we’re done optimizing this plan,

John Jantsch (10:33.902)

Yeah

Kyle Austin Young (10:59.812)

we end up feeling like it’s 90 % across the board. That’s still not a 90 % chance of success, but I believe it’s in the 70s. It’s a lot better.

John Jantsch (11:05.166)

Yeah. So, so do you find that you have to help people reframe this idea of failure even?

Kyle Austin Young (11:14.426)

Give me an example of what you mean by that.

John Jantsch (11:16.844)

Well, I mean, in some ways you’re, as I listened to you talk about the steps, you’re, you’re, you’re not saying that’s failures of possibility, but that it’s part of the equation. and a lot of people, you know, would have, I think some people would, would struggle with that idea. I, I’m not saying what you’re talking about doesn’t make sense, but just the mindset that a lot of people have that might be hard to overcome.

Kyle Austin Young (11:41.37)

Sure.

Absolutely. Failure is going to be part of the equation. One of the things that I encourage people to consider in the book is the power of multiple attempts. If you’re chasing a goal that’s really unlikely, often one of the most reliable ways to ultimately succeed is to try more than one time. I tell the story of the miracle on ice in the first chapter of the book. I got to interview Jack O’Callaghan who played on that 1980 hockey team that beat the Soviet Union. And a lot of people consider that a miracle. It’s been called the greatest sporting event of the 20th century, I believe, by Sports Illustrated.

John Jantsch (11:57.518)

Right.

Kyle Austin Young (12:14.028)

And as an individual event, it was really miraculous. But when you recognize that over the course of this Olympic rivalry, the United States played the Soviets nine times and won two, that’s not that remarkable. Winning two times out of nine isn’t unheard of. So was it surprising that they won the game they won? Sure. But the odds told us that we would expect them to win some games. And that’s ultimately what they did. And what’s interesting is when I interviewed Jack, he told me that in the locker room before they went out to take the ice for that game,

John Jantsch (12:23.842)

Mm-hmm. Right.

John Jantsch (12:35.18)

Yeah.

Kyle Austin Young (12:42.244)

Coach Herb Brooks gives this speech and there’s a movie about it and the movie has some quotes that are really powerful. What Jack told me is he said he doesn’t remember the exact words that were spoken. But he says he remembers that when he left the locker room, they’re trudging down to take the ice. He says he remembers leaving with the idea that his coach believed if we played them 10 times, they might beat us nine times, but they’re not going to beat us tonight. And so there was an expectation that failure was going to be a part of that, but they had an opportunity for tonight to be the exception. And ultimately it was.

John Jantsch (13:10.446)

I remember vividly watching that in my dorm room in college. does this, like a marathon I would call a long-term goal, particularly for somebody who hasn’t run one, right? They should start early, right? Can this be applied to short-term decisions as well?

Kyle Austin Young (13:14.956)

Amazing. I missed it by a few years, but I’m jealous.

Kyle Austin Young (13:24.666)

Sure. Sure.

Kyle Austin Young (13:33.166)

absolutely. You know, in the context of me trying to get that job, I just did this as I headed into an interview. It was going to all take place in a day. When we have something that needs to go right, one of the best things we can do to help it go right is think about what could go wrong. Ultimately, that’s what’s dragging our probability down. If you think about flipping a coin, let’s say you need it to land on heads, you have a 50 % chance of success. Why? Why don’t you have a 100 % chance of success? Well, because it might land on tails, and there’s a 50 % chance of that happening. Now, I don’t know how to rig a coin to make it…

do what I want it to do. But in life, a lot of times we can rig it or we can re-rig it in our favor. We can try to take the risk out of the bad outcomes, bring those odds over to our side.

John Jantsch (14:11.448)

So if somebody hasn’t thought this way, what’s kind some of the first things you try to help people? And again, I don’t know if you actually consult on this or teach courses on this as well, but what are some of the first things you try to do to get people to start putting this way of thinking? Because I think a lot of times these things are just mindset. So what do you get them to start thinking this way? What are some of the first things?

Kyle Austin Young (14:32.784)

Well, in the book, I tell people that I think there are four paths to success. One of them is some people just get lucky. I tell the story of Norma Jean Doherty. She’s working at an aviation munitions factory in the war, and a photographer comes to take pictures for a military magazine to inspire the troops. He notices Norma Jean, thinks she’s really beautiful, says, can I take some pictures for you for magazines that don’t have anything to do with the military? And she said, sure. She ultimately finds a lot of success as a model and then goes on to star as an actress under the name Marilyn Monroe, has just this enormously successful career.

That is certainly a success story. Is it a success story we should reverse engineer though? If I meet a young woman who’s coming to me for training or coaching rather, can you tell me what I can do to become a successful Hollywood star? Would I say, well, the first thing you need to do is get a job at an aviation munitions factory and hope that someday a military photographer stops by and notices how pretty you are and says, can I take some pictures of you? No, that probably wouldn’t be a very reliable path to success. So some people succeed through luck. They succeed even though the odds are bad, simply because we expect unlikely events to happen sometimes.

Some people succeed, they don’t beat the odds, but they play them. We think about entrepreneurs, there are some really famous examples of people who heard that nine out of 10 businesses fail, and that was actually what inspired them to start 10 businesses or 15 businesses, was the belief that they were going to experience those predicted failures, but they would also experience the predicted successes. Some people succeed because they have advantages, they have areas of tremendous strength in their lives, and so they try to lean into those goals.

John Jantsch (15:41.314)

you

Kyle Austin Young (15:54.084)

That can often be something that’s really wise for us is asking the question, what are some goals that are pretty high probability goals for me right now that might bring bigger accomplishments within reach? One of the goals that I had for years was ultimately getting a book deal and hopefully getting a big advance and being able to publish that to a mass audience with a major publisher. At the time when I set that goal, it wasn’t really realistic for me, but I was able to pursue smaller goals that changed my odds. One of them was writing for major publications.

John Jantsch (16:01.42)

Mm-hmm.

Kyle Austin Young (16:21.04)

As you mentioned, I’ve written for sites like HBR, Fast Company, Psychology Today. But one of my favorite things and one of the reasons I was so excited to have the opportunity to come on is it’s an exciting full circle moment for me. When I first decided that I was going to try to write for some of these respected publications, get my voice out there and ultimately position myself for things like a book deal, the first site that took me was the Duct Tape Marketing Blog. It was in 2015. I remember I was in my grandmother’s house at the time. They were having a garage sale. I was helping out when I got the response. I couldn’t even tell you where I was sitting.

John Jantsch (16:31.63)

You

John Jantsch (16:42.292)

the

Kyle Austin Young (16:49.742)

and it was such an exciting thing. So it’s an honor to be with you here today. So that’s the third path of success is people making the most of areas where they have good odds. The fourth path is probability hacking, doing everything you can to tilt the odds in your favor.

John Jantsch (16:50.286)

you

John Jantsch (17:01.006)

So, you know, I was going to ask you about resilience. And then you kind of threw in that story about the entrepreneurs starting 10 businesses, but what, what connection do you think with the framework and just the whole mindset of resilience? What does it play?

Kyle Austin Young (17:17.774)

Well, it’s incredibly important if you’re going to especially be pursuing the path of repeated attempts. In the book, I tell the story of Thomas Edison. He’s in a race to try to get valuable patents surrounding the incandescent lamp. If he can get them, it’ll be something that’s transformational for his career. And what this race came down to is he and these other people were all trying to find a practical filament. They needed something that could glow hot enough to emit light without catching on fire and without snuffing out really quickly to the point where it wasn’t worth it. What Edison did that was different than these other people…

John Jantsch (17:23.0)

Yeah.

John Jantsch (17:29.709)

Mm-hmm.

Kyle Austin Young (17:47.376)

is he actually experimented with 6,000 different plant materials to find the one that worked best. He didn’t try to divine the right answer. He didn’t try to guess the right answer. The answer turned out to be, in his context, carbonized bamboo. And I don’t know about you. That would not have been my first guess. If you said, what are we going to use as a filament? I would have said, I bet it’s carbonized bamboo. That’s not where I would have started. It’s not where he started either. It took 6,000 attempts. But ultimately, he had a clear definition of success. He had a stopwatch, so to speak. And he was able to run more experiments than anyone else. And because of that,

John Jantsch (17:54.144)

Mm-hmm.

John Jantsch (18:04.718)

the

Kyle Austin Young (18:15.364)

he found these unlikely answers. so resilience is a big part of that. Some of it comes from, we need to be confident that there is going to be a best answer out there. And in his case, it wasn’t, you know, it was comparative. He could be confident that one option out of the 6,000 would be the best out of the 6,000. And he liked his chance of creating a great product with a wider net when it came to ultimately trying to find the best filament than he did with somebody who’s only trying two or three things.

John Jantsch (18:27.982)

Thanks.

John Jantsch (18:41.526)

Yeah, and there’s obviously, I don’t know that it’s all true, but you hear these stories that people would ask him, gosh, aren’t you tired of failing so much? He said, no, I just have one more thing out of the way that I know is not the answer.

Kyle Austin Young (18:55.116)

He has a quote attributed to him that’s, to have a great idea, have a lot of them. And I think it’s that exact same mentality. It’s not about being the smartest person in the room necessarily. A lot of times it’s being the most generative. It’s being the person who’s the most prolific and who ultimately uncovers that unlikely good idea.

John Jantsch (18:58.936)

Yeah, yeah. Yeah.

John Jantsch (19:12.396)

Yeah. And, and, you know, there’s, there’s certainly a mentality out there. People want to, you know, take the easy path, get rich quick, you know, be famous, all the things that, people aspire to. And I don’t, you know, the, people that really get there, you know, they just show up and do the work every day for a long time. Sometimes.

Kyle Austin Young (19:29.614)

Well, it’s one of the dangers of reverse engineering, like I mentioned, you know, the Marilyn Monroe story, we kind of chuckle at that, but I think we’re doing similar things in our daily lives. We’ll find somebody who started a successful organization and turns out he drives a blue convertible. So I should buy a blue convertible because clearly that’s got to be playing a role in his success. What if he just got lucky? I’m not saying that they did, but we need to be really careful about what we reverse engineer because just because someone is seeing good results doesn’t mean that they got there through good decisions.

John Jantsch (19:31.874)

Yeah, yeah.

Right? Yeah.

John Jantsch (19:46.924)

Yeah.

John Jantsch (19:54.646)

Yeah. Well, and I think a lot of times we miss the 10 years before, before they blew up, right? Yeah, exactly. Well, Kyle, I appreciate you stopping by the Duct Tape Marketing Podcast. Is there someplace you’d invite people to find out more about your work and to perhaps pick up success is a numbers game.

Kyle Austin Young (19:58.778)

Sure, yeah, that kind of quote that most overnight successes are 20 years in the making, sure.

Kyle Austin Young (20:14.0)

You can get a copy of the book pretty much anywhere, Amazon, Barnes & Noble, directly on the Penguin Random House website. Be honored if you did that. If you want to connect with me personally, I think we’ll probably put my website in the show notes, just kyleaustinyoung.com. But what I’d prefer you do, honestly, this was something that was just kind of an unexpected blessing of this journey, is I heard someone who was encouraging people to find them on LinkedIn, and I thought, that’s a strange thing to do. I’ll throw that idea out too. And that was many interviews ago, but it’s turned into one of just the best parts of this, is pretty much every day I wake up and someone has

John Jantsch (20:25.134)

Mm-hmm.

Kyle Austin Young (20:43.118)

sent me a message saying, I heard you here, I heard you there, can I ask you a question? It’s led to some really engaging conversations that I’ve really enjoyed, some fun opportunities for collaboration for me. So feel free to find me, Kyle Austin Young on LinkedIn. I’d love to hear from you.

John Jantsch (20:45.1)

Okay.

John Jantsch (20:56.618)

Awesome. Well, again, appreciate you stopping by and hopefully we’ll maybe we’ll run into one of these days out there on the road.

Kyle Austin Young (21:02.16)

That’d be great. Thanks.

John Jantsch (00:01.218)

Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch. My guest today is Kyle Austin Young. He’s an award winning strategy consultant, speaker and writer who helps leaders, entrepreneurs and high achievers accomplish big, meaningful goals. His work centers on a unique decision-making and goal achievement framework that he calls probability hacking, a method designed to analyze and intentionally improve the odds of success in any pursuit. We’re going to talk about his newest book.

Success is a numbers game. Achieve bigger goals by changing the odds. So Kyle, welcome to the show.

Kyle Austin Young (00:37.348)

Thank you for having me. Honored to be here.

John Jantsch (00:39.278)

So I’m going to start with the premise that I’m sure you, I won’t be the first person to ask this question. I think a lot of times when people talk about goals, they think about hustle or mindset or heck even luck. You are saying it’s more about odds. What’s different in that shift?

Kyle Austin Young (00:59.15)

Yeah, let me give you sort of an example. Let’s say that we’ve set the goal of training to run a marathon. Let’s say that’s something that we’ve decided we want to accomplish and we hire a running coach and she says, I can get you ready in time, but you’re gonna have to do three things. I need you to eat, sleep, and train according to some specific regimens that I’m gonna create for you.

John Jantsch (01:02.872)

me

John Jantsch (01:14.829)

Mm-hmm.

Kyle Austin Young (01:16.334)

So let’s say that we know that one of these prerequisites is we’re to have to train according to some certain parameters. And so we identify some of the things that could go wrong, some of the things that might happen instead of what we want. And maybe we identify bad weather as something that could derail a training regimen. I’m currently preparing for a big wintery snowstorm. Let’s say that we identify injury as a potential risk, or maybe we identify that our kids might have a crisis that could overwhelm our schedule. So the question that I like to ask people is,

tell me how wanting to run a marathon is an antidote to any of those threats to our success. How does wanting to run a marathon change the weather? How does wanting to run a marathon prevent injury? How does wanting to run a marathon keep a crisis from happening in our kids’ lives? Certainly, we’re going to need a measure of commitment and hustle in order to be successful. But ultimately, what we’re going to really need is we need some creative solutions to the things that could keep us from getting what we want.

So I believe that we can understand probabilities similar to the way we’ve traditionally understood matter. It can’t be created or destroyed, but it can be transferred and rearranged. The odds of success, the odds that we want for our goal are currently hiding in our potential bad outcomes. When we identify what those things are and what we can do about them, we can tilt the odds in our favor.

John Jantsch (02:30.488)

So it’s all about quantum physics. Is that what you’re saying? So when you talk about moving matter around, was the first thought I had. Sure.

Kyle Austin Young (02:33.54)

Very little physics in the book. I don’t think I’ve ever taken a physics class.

Kyle Austin Young (02:40.418)

Well, I do think that there’s a lot of truth in the idea that a lot of people want to conjure good odds out of thin air. This idea that maybe I can wish myself into a better position. And I don’t think that’s true. I think that a lot of times when we’re pursuing a goal, we’re encouraged to think positive. Don’t worry about what could go wrong. If it’s meant to happen, it’ll happen. Just focus on the positive. I encourage people to do the exact opposite. I tell people to think negative. I tell people, for everything that has to go right in order for you to get what you want, identify the potential bad outcomes. Identify the things that could happen instead of what you want.

John Jantsch (02:55.8)

Thank

Kyle Austin Young (03:09.464)

and use your creativity to systematically de-risk your goals.

John Jantsch (03:13.826)

So in your bio, and I know in the book itself, you talk a lot about probability hacking. So let’s talk about what that is or how you define

Kyle Austin Young (03:22.916)

Yeah, I define probability hacking as doing exactly what we just did. It starts with getting an idea of what’s going to have to go right and then identifying what could go wrong and then looking for creative solutions. I’ll tell a different example. You know, when I first graduated from college, I wasn’t excited about the entry level positions that I was seeing. I wanted to try for something more ambitious. So I actually applied to become the product development director at a growing health organization. I was 21 years old. If hired, I was going to be managing people in their 50s, 60s, 70s, people with PhDs and master’s degrees.

a crazy thing to do, but I got an interview and I wanted to make the most of it. So even at that time, I did what I essentially do now for a living. I created what I call a success diagram. I only needed to get a job offer at that point. That was the only step left, but I looked at what are the potential bad outcomes that could happen instead of me getting that job offer. And so I identified three. And so I’m giving this example. You kind of had the quantum physics concern because there’s no numbers here. I’m just going to show you how we can do this at a story level. One of the risks I identified was they might not hire me because of how young I looked.

John Jantsch (04:15.054)

Bye.

Kyle Austin Young (04:21.54)

I might walk in and they take one look and say, he can’t lead this team. So one of the very practical things I did to combat that is I just grew a beard. I still have the beard today. It was something that made me look about 10 years older than I was. And I knew that if I could do that, it would maybe take the edge off of that concern a little bit. A second bad outcome that I identified, a potential bad outcome rather, was there might be concerns over my lack of experience, which were valid. I didn’t have a deep resume. I had just graduated from college. So what I did was I couldn’t lie. I wasn’t going to

John Jantsch (04:22.126)

Right.

Kyle Austin Young (04:49.54)

pretend that I had experience I didn’t have, but I wanted to show the quality of my thinking. So I actually typed up a plan for how I was going to turn this department around. It was so thick, I had to have it spiral bound. It was a book. And every person I went to and interviewed with, I gave them a copy of it. And the goal was when they would ask me questions about my past, I would just redirect it to be a conversation about the future. What experience do you have with whatever the case might be, product development? Great question. Here’s my plan for product development. Let’s talk about the vision that I have for this role if I’m given the opportunity.

The third potential bad outcome I identified was maybe they would be concerned that I couldn’t really get along with the existing team because there was just such a big generational gap. So I used a strategy that I’m still using today. It’s worked really well for me. I asked one of the people in the organization if the product development team had read any books recently as a group. She listed a few titles, I think it was three or four, and I went out and read every single one of them. And what that did is it gave me the ability to have conversations with the team that no other applicant could have. I understood their goals, I understood their jargon, I could make inside jokes.

John Jantsch (05:25.538)

Mm-hmm.

Kyle Austin Young (05:48.56)

There was a group interview where it was me and a bunch of people 20, 30 years older than me with a lot more experience trying to decide who was going to ultimately win the opportunity to lead this department. And one of the books that they read was called The Wuffy Factor. I don’t know if you remember that. was a book about how to, you remember the Wuffy? It was about how brands are in social capital. This was close to 15 years ago. And I remember being in that interview and I said, you know, I think this idea that we’re discussing could help us get a lot of Wuffy.

John Jantsch (05:57.934)

Right.

I remember saying that, yeah, yeah.

Kyle Austin Young (06:11.632)

And I remember looking around and these other applicants, their eyes are bugging out of their heads. What on earth did he just say? You know, is he feeling, okay, what does he mean? We’re going to get a lot of wealthy out of this. But the existing team members, they were all laughing and nodding along. They knew exactly what I was talking about. We were reading the same books. So when all was said and done, I got that job. At 21 years old, I became the product development director for a health organization. It dramatically accelerated my career, but it started with this idea of probability hacking. It started with getting clear on what I wanted and getting clear on what was going to have to go right. Then thinking negatively,

identifying the risks to my success and not resorting to desire as an antidote to uncertainty, but instead using my creativity to solve those problems.

John Jantsch (06:49.006)

So you gave very specific details and steps of what you did, but it sounded, it started to sound a bit like a framework, which I know you have in the book. So were those steps that you gave me a part of that framework? Do you want to outline what that framework is?

Kyle Austin Young (07:04.41)

Sure, I encourage people to start by creating what I call a success diagram. A success diagram is you write down what’s the goal, what do I want to accomplish? I do that at the top right of the page. And then to the left, I just try to list out everything that’s gonna have to go right in order for me to get what I want. So it might be run a marathon. And what I call critical points, the prerequisites to my success are eat according to the regimen my coach gives me, sleep according to the regimen she gives me, train according to the regimen she gives me. So now I have the path, I have the destination.

And then for each one of those things that has to go right, I try to identify the potential bad outcomes. These aren’t just things that could go wrong, they’re alternate outcomes to success. Things that would be so significant they would completely derail the goal if any of them were to come true. After I have those mapped out, I try to just assign a level of risk to each of them. Is this a low risk potential bad outcome, a medium risk, a high risk, so they know how to prioritize? And then probability hacking again is using our creativity to try to find solutions to that. If I’m concerned about

you know, inclement weather derailing my training routine, I might need a treadmill indoors or need to find some alternate exercises that can allow me to build my fitness on days when I can’t go for a run. If I’m concerned about scheduling issues, something happening at my kid’s school, then I might want to train first thing in the morning or I might want to buy an extra pair of running shoes to keep in the car so that I can train at a park if I need to, if my day gets derailed.

John Jantsch (08:20.034)

In a lot of ways, what I’m hearing you describe is, I mean, think there are a lot of people that have mapped out the plan to run the marathon. mean, you can buy books, entire books, will tell you exactly what to do on day one, day two. But what you’re saying a lot of people miss is integrating the whole, you know, of life. And I think in a lot of ways, you’re really just asking people to step back and you’re calling it what could go wrong. But what you’re really doing is saying, hey, you have to have a grasp of reality.

Kyle Austin Young (08:31.29)

Sure.

Kyle Austin Young (08:49.764)

I think you do have to have a grasp of reality. I think that when we consider these statistics that are floating around all the time, just how many people fail at their New Year’s resolutions, how this vast majority of mergers and acquisitions fail to create lasting value for shareholders, how many new businesses will ultimately fail in the first few years after their existence, we start to recognize that it’s because we haven’t stopped to consider the things that could go wrong. And I’ll demonstrate that with just a little bit of numbers. Let’s use that marathon example. There’s three things that have to go right. I need to eat, sleep, and train according to a certain regimen.

John Jantsch (08:51.307)

me

John Jantsch (08:57.139)

Mm-hmm. Right.

John Jantsch (09:13.763)

Mm-hmm.

Kyle Austin Young (09:19.14)

Well, let’s take some imaginary numbers and try to estimate how likely we are to accomplish each of those three things. Maybe we think it’s 70 % across the board. 70 % chance I’ll stick with the diet, 70 % chance I’ll sleep the way I’m supposed to, 70 % chance I’ll train the way I’m supposed to. What a lot of people do is they fall into a trap called averaging. If they feel good about the individual prerequisites, they feel good about the goal as a whole. That’s not actually logically sound, it’s not mathematically sound. What we have to do is multiply those numbers together to find our overall odds of success.

John Jantsch (09:45.261)

Yes.

Kyle Austin Young (09:47.204)

And if we do that, we find that even though we feel really good about each of these things, 70 % across the board, our overall odds of being ready on race day are only 34%. And that I believe explains a lot of the dysfunction in our world. Why are people failing at goals and wondering, how did this not go the way that I expected it to? I felt good about each individual step. Well, you averaged in your head. You didn’t take the time to understand what your overall odds were. And because of that, maybe you didn’t pay as much attention to your opportunity to change your odds as you could have. Maybe you didn’t get that grasp on reality exactly like what you said.

John Jantsch (10:14.926)

Thank

Kyle Austin Young (10:16.27)

and try to the odds in your favor.

John Jantsch (10:18.766)

Is there any, do you ever run the risk or do you find that people might, like if I sat down thought, oh, my odds of actually being prepared on race day is only in the 30 % range, is there any chance that I say, why bother?

Kyle Austin Young (10:32.538)

There could be, but if we’re taking the time to think negative and identify the bad outcomes that are dragging those odds down, then we can use our creativity and see if we can’t change those numbers, at least in how we understand them, to look like something that’s more optimistic. You if we are using our creativity to address the risk of bad weather when we need to train, or address the risk of injury, or address the risk of our schedule being sabotaged, then we can ultimately run the numbers again. And maybe by the time we’re done optimizing this plan,

John Jantsch (10:33.902)

Yeah

Kyle Austin Young (10:59.812)

we end up feeling like it’s 90 % across the board. That’s still not a 90 % chance of success, but I believe it’s in the 70s. It’s a lot better.

John Jantsch (11:05.166)

Yeah. So, so do you find that you have to help people reframe this idea of failure even?

Kyle Austin Young (11:14.426)

Give me an example of what you mean by that.

John Jantsch (11:16.844)

Well, I mean, in some ways you’re, as I listened to you talk about the steps, you’re, you’re, you’re not saying that’s failures of possibility, but that it’s part of the equation. and a lot of people, you know, would have, I think some people would, would struggle with that idea. I, I’m not saying what you’re talking about doesn’t make sense, but just the mindset that a lot of people have that might be hard to overcome.

Kyle Austin Young (11:41.37)

Sure.

Absolutely. Failure is going to be part of the equation. One of the things that I encourage people to consider in the book is the power of multiple attempts. If you’re chasing a goal that’s really unlikely, often one of the most reliable ways to ultimately succeed is to try more than one time. I tell the story of the miracle on ice in the first chapter of the book. I got to interview Jack O’Callaghan who played on that 1980 hockey team that beat the Soviet Union. And a lot of people consider that a miracle. It’s been called the greatest sporting event of the 20th century, I believe, by Sports Illustrated.

John Jantsch (11:57.518)

Right.

Kyle Austin Young (12:14.028)

And as an individual event, it was really miraculous. But when you recognize that over the course of this Olympic rivalry, the United States played the Soviets nine times and won two, that’s not that remarkable. Winning two times out of nine isn’t unheard of. So was it surprising that they won the game they won? Sure. But the odds told us that we would expect them to win some games. And that’s ultimately what they did. And what’s interesting is when I interviewed Jack, he told me that in the locker room before they went out to take the ice for that game,

John Jantsch (12:23.842)

Mm-hmm. Right.

John Jantsch (12:35.18)

Yeah.

Kyle Austin Young (12:42.244)

Coach Herb Brooks gives this speech and there’s a movie about it and the movie has some quotes that are really powerful. What Jack told me is he said he doesn’t remember the exact words that were spoken. But he says he remembers that when he left the locker room, they’re trudging down to take the ice. He says he remembers leaving with the idea that his coach believed if we played them 10 times, they might beat us nine times, but they’re not going to beat us tonight. And so there was an expectation that failure was going to be a part of that, but they had an opportunity for tonight to be the exception. And ultimately it was.

John Jantsch (13:10.446)

I remember vividly watching that in my dorm room in college. does this, like a marathon I would call a long-term goal, particularly for somebody who hasn’t run one, right? They should start early, right? Can this be applied to short-term decisions as well?

Kyle Austin Young (13:14.956)

Amazing. I missed it by a few years, but I’m jealous.

Kyle Austin Young (13:24.666)

Sure. Sure.

Kyle Austin Young (13:33.166)

absolutely. You know, in the context of me trying to get that job, I just did this as I headed into an interview. It was going to all take place in a day. When we have something that needs to go right, one of the best things we can do to help it go right is think about what could go wrong. Ultimately, that’s what’s dragging our probability down. If you think about flipping a coin, let’s say you need it to land on heads, you have a 50 % chance of success. Why? Why don’t you have a 100 % chance of success? Well, because it might land on tails, and there’s a 50 % chance of that happening. Now, I don’t know how to rig a coin to make it…

do what I want it to do. But in life, a lot of times we can rig it or we can re-rig it in our favor. We can try to take the risk out of the bad outcomes, bring those odds over to our side.

John Jantsch (14:11.448)

So if somebody hasn’t thought this way, what’s kind some of the first things you try to help people? And again, I don’t know if you actually consult on this or teach courses on this as well, but what are some of the first things you try to do to get people to start putting this way of thinking? Because I think a lot of times these things are just mindset. So what do you get them to start thinking this way? What are some of the first things?

Kyle Austin Young (14:32.784)

Well, in the book, I tell people that I think there are four paths to success. One of them is some people just get lucky. I tell the story of Norma Jean Doherty. She’s working at an aviation munitions factory in the war, and a photographer comes to take pictures for a military magazine to inspire the troops. He notices Norma Jean, thinks she’s really beautiful, says, can I take some pictures for you for magazines that don’t have anything to do with the military? And she said, sure. She ultimately finds a lot of success as a model and then goes on to star as an actress under the name Marilyn Monroe, has just this enormously successful career.

That is certainly a success story. Is it a success story we should reverse engineer though? If I meet a young woman who’s coming to me for training or coaching rather, can you tell me what I can do to become a successful Hollywood star? Would I say, well, the first thing you need to do is get a job at an aviation munitions factory and hope that someday a military photographer stops by and notices how pretty you are and says, can I take some pictures of you? No, that probably wouldn’t be a very reliable path to success. So some people succeed through luck. They succeed even though the odds are bad, simply because we expect unlikely events to happen sometimes.

Some people succeed, they don’t beat the odds, but they play them. We think about entrepreneurs, there are some really famous examples of people who heard that nine out of 10 businesses fail, and that was actually what inspired them to start 10 businesses or 15 businesses, was the belief that they were going to experience those predicted failures, but they would also experience the predicted successes. Some people succeed because they have advantages, they have areas of tremendous strength in their lives, and so they try to lean into those goals.

John Jantsch (15:41.314)

you

Kyle Austin Young (15:54.084)

That can often be something that’s really wise for us is asking the question, what are some goals that are pretty high probability goals for me right now that might bring bigger accomplishments within reach? One of the goals that I had for years was ultimately getting a book deal and hopefully getting a big advance and being able to publish that to a mass audience with a major publisher. At the time when I set that goal, it wasn’t really realistic for me, but I was able to pursue smaller goals that changed my odds. One of them was writing for major publications.

John Jantsch (16:01.42)

Mm-hmm.

Kyle Austin Young (16:21.04)

As you mentioned, I’ve written for sites like HBR, Fast Company, Psychology Today. But one of my favorite things and one of the reasons I was so excited to have the opportunity to come on is it’s an exciting full circle moment for me. When I first decided that I was going to try to write for some of these respected publications, get my voice out there and ultimately position myself for things like a book deal, the first site that took me was the Duct Tape Marketing Blog. It was in 2015. I remember I was in my grandmother’s house at the time. They were having a garage sale. I was helping out when I got the response. I couldn’t even tell you where I was sitting.

John Jantsch (16:31.63)

You

John Jantsch (16:42.292)

the

Kyle Austin Young (16:49.742)

and it was such an exciting thing. So it’s an honor to be with you here today. So that’s the third path of success is people making the most of areas where they have good odds. The fourth path is probability hacking, doing everything you can to tilt the odds in your favor.

John Jantsch (16:50.286)

you

John Jantsch (17:01.006)

So, you know, I was going to ask you about resilience. And then you kind of threw in that story about the entrepreneurs starting 10 businesses, but what, what connection do you think with the framework and just the whole mindset of resilience? What does it play?

Kyle Austin Young (17:17.774)

Well, it’s incredibly important if you’re going to especially be pursuing the path of repeated attempts. In the book, I tell the story of Thomas Edison. He’s in a race to try to get valuable patents surrounding the incandescent lamp. If he can get them, it’ll be something that’s transformational for his career. And what this race came down to is he and these other people were all trying to find a practical filament. They needed something that could glow hot enough to emit light without catching on fire and without snuffing out really quickly to the point where it wasn’t worth it. What Edison did that was different than these other people…

John Jantsch (17:23.0)

Yeah.

John Jantsch (17:29.709)

Mm-hmm.

Kyle Austin Young (17:47.376)

is he actually experimented with 6,000 different plant materials to find the one that worked best. He didn’t try to divine the right answer. He didn’t try to guess the right answer. The answer turned out to be, in his context, carbonized bamboo. And I don’t know about you. That would not have been my first guess. If you said, what are we going to use as a filament? I would have said, I bet it’s carbonized bamboo. That’s not where I would have started. It’s not where he started either. It took 6,000 attempts. But ultimately, he had a clear definition of success. He had a stopwatch, so to speak. And he was able to run more experiments than anyone else. And because of that,

John Jantsch (17:54.144)

Mm-hmm.

John Jantsch (18:04.718)

the

Kyle Austin Young (18:15.364)

he found these unlikely answers. so resilience is a big part of that. Some of it comes from, we need to be confident that there is going to be a best answer out there. And in his case, it wasn’t, you know, it was comparative. He could be confident that one option out of the 6,000 would be the best out of the 6,000. And he liked his chance of creating a great product with a wider net when it came to ultimately trying to find the best filament than he did with somebody who’s only trying two or three things.

John Jantsch (18:27.982)

Thanks.

John Jantsch (18:41.526)

Yeah, and there’s obviously, I don’t know that it’s all true, but you hear these stories that people would ask him, gosh, aren’t you tired of failing so much? He said, no, I just have one more thing out of the way that I know is not the answer.

Kyle Austin Young (18:55.116)

He has a quote attributed to him that’s, to have a great idea, have a lot of them. And I think it’s that exact same mentality. It’s not about being the smartest person in the room necessarily. A lot of times it’s being the most generative. It’s being the person who’s the most prolific and who ultimately uncovers that unlikely good idea.

John Jantsch (18:58.936)

Yeah, yeah. Yeah.

John Jantsch (19:12.396)

Yeah. And, and, you know, there’s, there’s certainly a mentality out there. People want to, you know, take the easy path, get rich quick, you know, be famous, all the things that, people aspire to. And I don’t, you know, the, people that really get there, you know, they just show up and do the work every day for a long time. Sometimes.

Kyle Austin Young (19:29.614)

Well, it’s one of the dangers of reverse engineering, like I mentioned, you know, the Marilyn Monroe story, we kind of chuckle at that, but I think we’re doing similar things in our daily lives. We’ll find somebody who started a successful organization and turns out he drives a blue convertible. So I should buy a blue convertible because clearly that’s got to be playing a role in his success. What if he just got lucky? I’m not saying that they did, but we need to be really careful about what we reverse engineer because just because someone is seeing good results doesn’t mean that they got there through good decisions.

John Jantsch (19:31.874)

Yeah, yeah.

Right? Yeah.

John Jantsch (19:46.924)

Yeah.

John Jantsch (19:54.646)

Yeah. Well, and I think a lot of times we miss the 10 years before, before they blew up, right? Yeah, exactly. Well, Kyle, I appreciate you stopping by the Duct Tape Marketing Podcast. Is there someplace you’d invite people to find out more about your work and to perhaps pick up success is a numbers game.

Kyle Austin Young (19:58.778)

Sure, yeah, that kind of quote that most overnight successes are 20 years in the making, sure.

Kyle Austin Young (20:14.0)

You can get a copy of the book pretty much anywhere, Amazon, Barnes & Noble, directly on the Penguin Random House website. Be honored if you did that. If you want to connect with me personally, I think we’ll probably put my website in the show notes, just kyleaustinyoung.com. But what I’d prefer you do, honestly, this was something that was just kind of an unexpected blessing of this journey, is I heard someone who was encouraging people to find them on LinkedIn, and I thought, that’s a strange thing to do. I’ll throw that idea out too. And that was many interviews ago, but it’s turned into one of just the best parts of this, is pretty much every day I wake up and someone has

John Jantsch (20:25.134)

Mm-hmm.

Kyle Austin Young (20:43.118)

sent me a message saying, I heard you here, I heard you there, can I ask you a question? It’s led to some really engaging conversations that I’ve really enjoyed, some fun opportunities for collaboration for me. So feel free to find me, Kyle Austin Young on LinkedIn. I’d love to hear from you.

John Jantsch (20:45.1)

Okay.

John Jantsch (20:56.618)

Awesome. Well, again, appreciate you stopping by and hopefully we’ll maybe we’ll run into one of these days out there on the road.

Kyle Austin Young (21:02.16)

That’d be great. Thanks.

John Jantsch (00:01.442)

Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch and my guest today is Peter Benei. He is a marketing leader and strategist with 20 plus years of experience as a CMO for tech scale-ups and startups. He co-founded AI Ready CMO, a platform and newsletter focused on helping marketing leaders adopt AI strategically, not just tool by tool, but through frameworks, case studies and community learning.

Peter Benei (00:01.57)

Thanks.

John Jantsch (00:30.39)

So guess what we’re going to talk about today? AI. Peter, welcome to the show.

Peter Benei (00:34.634)

Welcome and thanks for inviting me.

John Jantsch (00:38.028)

So given that you and I were just talking off air, you know, I’ve got 30 plus years, you’ve got 20 plus years, how in your mind has, does AI or the advent of AI different than say, websites and social media and search, you know, that kind of came along as tool? Would you say that it’s just another flavor or is it fundamentally different?

Peter Benei (00:43.341)

Yeah.

Peter Benei (01:04.052)

both, I guess. I had my own agency as well. Jesus, 20 years ago. and it was a social media agency. So at that time it was like, so Facebook business pages just got introduced and everyone was talking about the clue train manifesto markets are conversations and you know, this kind of stuff, social media, web two. I don’t know if you’re familiar with the market or Brian Solis.

John Jantsch (01:05.879)

Yeah.

John Jantsch (01:19.584)

Yeah.

John Jantsch (01:24.384)

Yeah. Yeah. Yeah. Yeah. Yeah.

Peter Benei (01:33.262)

Yeah, he was just about talking about the conversational prism and I don’t know. So everyone was talking about like, know, social media is a thing. And we had this agency, which was a social media agency. But again, that was a new thing. I don’t really think that the whole AI, whatever it is right now is…

John Jantsch (01:33.432)

Of course, yeah, Brian’s been on the show.

Peter Benei (02:02.4)

is new in a sense of tools and technology for marketers. These are just things that we need to learn and adapt to in general sense, like we did for, I don’t know, Facebook business pages at that time or, I don’t know, Squarespace websites. you can drag and drop websites again now. That’s interesting. Although I think the business model for agencies and marketing teams will be fundamentally changed

John Jantsch (02:22.53)

Yeah.

Peter Benei (02:32.184)

because of this new AI tool, AI capabilities, AI agent, whatever, AI. And I think that will be interesting to see. again, agencies also changed and marketing teams also changed 10, five, 20 years ago. So I think we just need to be familiar and open to adapt to this new change. So I don’t…

John Jantsch (03:00.31)

Well…

Peter Benei (03:01.078)

dramatize or strategize or panic around this. You just need to adapt.

John Jantsch (03:08.056)

Yeah, it’s funny. There was a period of time where you had social media marketing agencies and digital marketing agencies, right? It was just like, oh no, we’re this flavor. And now it’s just like, no, it’s all just marketing. Right. So what are the things you write about a lot? And, and I, you know, I’m a subscriber to your newsletter and I really, there are a lot of people out there writing about AI hype, you know, like look at what this thing could do. But I think you guys have take a very,

Peter Benei (03:12.206)

Hmm?

Peter Benei (03:19.693)

Yes.

Peter Benei (03:25.944)

Thank you.

John Jantsch (03:35.352)

Like you said, not necessarily a dramatic hype approach, a very almost stand back approach of saying, look, we have to remain strategic. Human beings have a role, but maybe it’s changed. And so I really appreciate that take. So let’s get in a little bit to the changing, like the AI plus strategy, you know, plus humans approach, because there’s certainly a lot of hand wringing right now around all these jobs that are going to be wiped out.

What are people going to do? So what do you, let’s just divide it. What do you think is going to go away that these tools actually do better than humans? And what do you think is going to actually stay and perhaps not for a long time be replaced by humans or by machines.

Peter Benei (04:05.486)

Thanks.

Peter Benei (04:21.922)

No, that’s a tempting and also interesting question. One thing that I want to reflect quickly, the focus on non-hype bullshit and sorry for calling that way, non-hype framing of this whole entire new trend was also personal choice of ours with the newsletter, but also a strategic choice as well.

Obviously everyone is hyping around this whole thing. we are personally, we are getting a little bit older, I guess. And we are just not interested in the, the, in the defocusing of our audiences. So we made the conscious decision to kind of like stand still and observe a little bit more with a strategic eye. So that’s one thing. Second.

John Jantsch (05:09.921)

Mm-hmm.

Peter Benei (05:18.232)

To your question, I would love to have an answer, but I’m not afraid to say that I don’t know. think during these times that are changing, it’s really hard to know what will happen. And we are just migrating, by the way, the news that are to another platform. And I had to reread the old stuff that we wrote. When I say old, like half a year ago.

John Jantsch (05:37.858)

Mm-hmm.

John Jantsch (05:47.832)

All right.

Peter Benei (05:48.174)

And that will be a context to your answer, by the way. And I just read what we’d wrote like half a year ago and everything was so beginning at that stage still. Everything changed so fast within a couple of months. New tools came out, new concepts introduced to the public. And I’m not talking about like agents, like more like, know.

John Jantsch (06:04.375)

Mm-hmm.

Peter Benei (06:14.818)

working together with AI, human in the loop, and these kind of stuff. It’s so hard to predict because within this small time frame, everything has changed. I think what we can do to answer this question, and sorry for it, it takes a little bit longer, is that to nail down the basics that we think that it will be changing. And I think there are a couple of things that will change. And one that I’m…

almost 100 % sure it will change is that production of marketing materials and like marketing production in a sense, like content production, shall we say, will be either fully automated or it will not come with a high barrier of entry. It doesn’t have a high barrier of entry right now either, but it will have like a minimum barrier of entry with AI.

John Jantsch (06:54.614)

Mm-hmm. Mm-hmm.

Peter Benei (07:14.254)

That means a lot for agencies, by the way, for marketing teams, because we create, mean, like 80 % of our work as marketers are creating content. Now, if the content creation is almost automated by AI, what do we do? Right? That’s the question. Now I don’t have the answer, but I’m sure that we won’t create that much and that amount of content within our workload and work time.

Second, AI is getting perfect or better, shall we say. It’s always, know, tomorrow’s AI is 10x better than today’s AI. But it’s still not perfect. And the reason why it’s not perfect is that it still needs the human, us, to course, supervise, review, edit, whatever. So I think the…

human in the loop or human in the addition working with the AI, it will matter for now, for a couple of years at least. And third, we need to think that if production is not our job anymore, but we still need it, then where do we need it? And I think that’s the answer for your question here, that we need to be able to form strategies.

And what is the strategy, by the way, understanding the client need with empathy and suggest process to achieve the goals. are goals and that’s it. Pretty much that’s the bare bones, simple strategy. How do we produce more? sorry. How do we produce better content? Because production wise, it will be automated, but it still has to be good. We need taste.

John Jantsch (08:56.45)

Right.

John Jantsch (09:09.698)

Right.

Peter Benei (09:11.106)

We need quality, we need judgment, we review supervision. And how do we work better with AI is that if we understand the workflows and the processes as a kind of like operator of the entire show. So I think strategy, like empathy, taste and operational efficiency or workflow knowledge should be…

and will be important for marketers. And I’m safe to say these.

John Jantsch (09:44.822)

Yeah, you, you. Well, and I think you raise a real, I think at least right now, one of the differentiators, the barrier to produce, to producing, quantity is gone. however, I think the barrier to producing quality is still a real differentiator.

Peter Benei (10:03.042)

Yeah. Yeah, I agree. agree. And it just, know, AI just like highlighted how not many of us have taste and how not many of us can produce great content and how most of the content that we’ve used so far anyway was, well, wouldn’t say garbage, but like, you know, mediocre. And I think it’s super important to…

to highlight that previously you needed resources to produce high quality content. So if you wanted to do a Super Bowl level advertising, you needed DDB or or or whoever big agency. If you wanted to do a global media campaign, you needed a media agency or an insane marketing budget to go with that.

John Jantsch (10:37.901)

Yes.

Peter Benei (11:02.638)

If you wanted to produce a content library of whatever you have, like 100 eBooks or shit, you need 10, 50, whatever, copywriters or marketers to do that. Similarly happening in other industries. So if you wanted to do the new John Wick movie, you needed a Hollywood studio and so on. can go on and on.

John Jantsch (11:18.338)

Thanks.

Peter Benei (11:33.184)

Now you don’t need these resources. You need a laptop and an idea and I don’t know, hundred dollars for API credits. And pretty much that’s it. That’s it. That’s all you need. And judgment and taste and strategic mindset. And, know, these kinds of stuff that are human in innate human values and abilities, which AI cannot produce.

John Jantsch (11:36.205)

Mm-hmm.

John Jantsch (12:02.658)

Well, so that begs the question then, if we are going to still have humans involved, do we need different humans? A lot of us. If we built an organization, say, to produce stuff, you know, the copywriters, the graphic designers, that their whole output was the stuff, do we now need to hire for taste and for judgment and for brand intuition?

Peter Benei (12:17.602)

Mm-hmm.

Peter Benei (12:27.83)

I yes. I’m not the person who will tell you otherwise. And I’m also not the person who is in the business who helps you to do that. But if I would be in the business, I would immediately start some sort of like a training company or anything around that that helps people who have like basic skills through studies. Like, I don’t know.

John Jantsch (12:28.92)

the

Peter Benei (12:57.806)

creative arts or whatever, and upgrading them to be able to use those skills in a refined manner for multiple purposes. In our case, marketing. So yeah, people and companies should hire Prudence.

John Jantsch (12:59.661)

Right.

John Jantsch (13:13.496)

And I think I’ve actually seen on your website, aren’t you producing some courses or some master classes or something around those? Yeah, yeah, okay.

Peter Benei (13:21.302)

Yeah, we do some workshops. We do some workshops, but we are not a training company. So, so we didn’t within AI ready CMO, if you like pave to go to get a paid member, you obviously have access to some sort of like a workshop training program and some studies, but we are not a training.

John Jantsch (13:26.551)

Yeah, yeah.

John Jantsch (13:40.994)

Right, right. Yeah, okay. So, would you… If somebody was, I don’t know, maybe coming out of school now or maybe trying to change careers or something, are there some roles or functions that you would say, hey, you should spend your time up-leveling your skills in this area?

Peter Benei (13:42.924)

And I don’t want to be a training company.

Peter Benei (13:52.334)

Hmm?

Peter Benei (14:03.608)

So I’m 44. That will be a long shot, I’m 44 and many of my friends have kids who are like 15 or 10 or 15 or 20 sometimes. And they all talk about the same thing. I like full honesty.

John Jantsch (14:30.84)

Mm-hmm.

Peter Benei (14:33.39)

They talk about what will these kids will do in five to 10 years, what kind of careers they will pursue and so on and so on. They are families. So I usually talk with the dads, obviously, and they are talking about, I need to send my kid to a university or college or whatever. I live in Europe, so I don’t know, they send it to Vienna or something. And how…

How should I pick which university they should go in and so on and so on? How should I help them? And they are clueless. And usually the close to good answer that I see, and again, this is a personal opinion, so treat it as is, usually the ones that are sending their kids to some sort of like art, history,

John Jantsch (15:10.776)

Mm-hmm.

Right.

John Jantsch (15:31.512)

Mm-hmm.

Peter Benei (15:32.782)

Literally something around these like soft things, which we call soft skills or soft studies.

John Jantsch (15:37.376)

Mm-hmm.

John Jantsch (15:41.495)

Mm-hmm.

Peter Benei (15:44.692)

I wouldn’t send my kid to engineering school right now. I wouldn’t send my kid to learn that become a developer or a lawyer or not even a doctor probably. I don’t think that these, I mean, these professions will exist obviously, but it will have a really huge competition that only the finest one will succeed or will be needed.

but if you have like a general arts degree or something around that, know usually, you know, treated as totally useless. I have one by the way. but still, so I studied history and sociology pretty much useless, I guess, but still. and I think these, these studies might be something that can be valuable because they, they teach you the basics of.

John Jantsch (16:22.922)

Right?

Peter Benei (16:43.64)

how to read, how to judge aesthetic things, and how to think critically, yes. How to think in context, so like historical context, let’s say. And I think these baseline knowledge skills, let’s say, I wouldn’t call them skills, but these things will be in, yes.

John Jantsch (16:49.89)

I to think critically.

John Jantsch (17:08.704)

It’s exposure really more than anything else, right? Yeah.

Peter Benei (17:11.746)

These will be inherently valuable than knowing the latest legal, whatever it is.

John Jantsch (17:14.274)

Yeah, yeah.

John Jantsch (17:19.308)

Yeah, yeah, yeah, which can be, yeah, queued up. How about CMOs? Are you, do you see that role going away? Do you see it, you know, changing inside of organizations to where it will not only look different, but it will have a different function?

Peter Benei (17:22.541)

Yes.

Peter Benei (17:38.232)

So we preach at AERA, the CMO is that the CMO role is becoming more like an orchestrator who is leading and creating these environments of workflows where people work together with AI and AI automation. And from the marketing org chart, like, know, junior, mid-manager, specialist.

John Jantsch (17:47.81)

Mm-hmm.

Peter Benei (18:07.128)

head off whatever and see. I do think that the CMO role will be the last one who will fall. Juniors probably will have the hardest time, especially, and also mid managers and specialists, because some of them need to pivot into something else because AI will just simply eat their field of expertise there.

but those people who are able to manage not just people, but workflows together. mixing the soft skills with, I wouldn’t say engineering level skills of workflow engineering, but more like, you know, operational level. I think these people will be valuable and these people will be the CMOs I think. But if you were a CMO and only created the marketing budget and.

John Jantsch (18:53.516)

Mm-hmm.

Peter Benei (19:06.306)

delegated the tasks and that’s it. Yeah, you probably will have a harder time in the upcoming years and you need to learn workflow efficiency, operational level execute and you know, these kinds of Or if you are on the other side, more like an operational person, you probably need to learn a little bit more soft skills and judgment and taste and you know, these kinds of stuff that we talked about so far.

John Jantsch (19:35.124)

So I want end on one kind of, there’s a bit of been a bit of a rant for me and I’m curious where you land on this. I think a lot of people were jumping at, my AI tool stack is these 17 tools because they all do one thing really well. And I think what I’ve said all along is I think the Googles and the Microsofts of the world are going to basically figure out how to build all of those best of class tools into their

Peter Benei (19:41.774)

Please.

Peter Benei (19:51.342)

Hmm.

Peter Benei (20:03.448)

Agree.

John Jantsch (20:04.696)

into their work tool that you buy for one price or that you’re already buying that now is just $10 more a month. And they will really kind of wipe out a lot of these one-off tools. I’m curious what you think of that.

Peter Benei (20:10.926)

I agree.

Peter Benei (20:18.094)

100%. I mean, this will be a hard argument because I 100 % agree with you. I can share you two examples. Two examples and one explanation on why people think that. I mean, especially, know, C level people and decision makers, they love throwing resources on problems. So yeah, they have like a tool.

John Jantsch (20:43.352)

Mm-hmm.

Peter Benei (20:48.174)

abundance, and they, and they buy shiny new tools every day. that’s fine. We understand it’s obviously not the right call. and even, even they don’t, they know it usually. and the two examples are, are simple ones. One, you actually mentioned off of air that you read the latest article that we, that we published. I mean, it’s not rocket science judge, just a Claude Cowork, came out.

John Jantsch (21:16.941)

Yes.

Peter Benei (21:18.282)

A funny thing, by the way, did Claude did it. mean, the Anthropic team did it with Claude code within half, one and a half a week. And no line of code were written by any engineers, all AI. So the learning there is that most of the tools will be irrelevant because startups

John Jantsch (21:29.848)

Mm.

John Jantsch (21:34.934)

Yes.

Peter Benei (21:45.674)

And AI tools just die every day because new tools will come out. Also don’t forget that the big ones, Google and the others, they have infinite resources, like infinite. They have infinite training data and AI lives on data. So just like one simple AI feature added to Google ads, let’s say.

We’ll probably kill 90 % of the AI tools out there right now overnight.

John Jantsch (22:20.972)

Well, they also, know, one thing people underestimate, they also have all the hardware.

Peter Benei (22:25.216)

And also the hardware. Well, in a sense business, that hardware doesn’t really matter that much, more like the data, but yeah, the hardware is important too. And the second thing is that, well, I’m really proud of it because it happened today. So sorry for sharing it with everyone right now on this podcast, but I built a content repurposing application. You literally, it does…

John Jantsch (22:26.584)

So it doesn’t cost them anything.

John Jantsch (22:35.49)

Yeah. Yeah.

John Jantsch (22:45.208)

You

Peter Benei (22:54.956)

A simple thing, you give an RSS feed to the application, in our case, our newsletter. We are only two people. So we don’t have social media managers and stuff. And because most of the content that we do is news-driven, so every day we publish something new. We cannot batch write stuff pre-time. So we only know the content on the same day.

and we need to share it on X and everywhere. And we spend a lot of time to repurposing this type of content, even if we use AI. So this app actually takes everything that we have, new posts, and repurpose it on different platforms. It self-learns, it does everything. It’s fully automated, it’s amazing. It has a UX, everything.

and I built it under an hour while I having breakfast at my kitchen table. I’m not kidding. And I don’t know how to code at all. Like I never coded a single line of code ever. And I will probably never will. Claude did it. just why prompting it. So the reason why I’m telling this, thing is that it’s so easy to build up something new now.

John Jantsch (23:58.336)

Yeah.

Peter Benei (24:21.134)

even for personal use that you probably end up and that’s like a wild guess and more like a futurism. But I might guess that within a year or two, we don’t really even have like small sasses for most companies. People just, you know, ramp up their own applications for their own computer, for their own personal use, for their own agency, for their own clients within an hour.

John Jantsch (24:21.186)

Yeah. Right.

Peter Benei (24:50.508)

works fine just for them.

John Jantsch (24:53.016)

Yes. Yes, yes.

Peter Benei (24:54.382)

So it’s interesting. So short answer to your question. mean, don’t really bother subscribing to 20-something AI tools. Probably 95 % of them will be extinct within a year or two and substitute by Gemini or other Google products or whatever. Or second answer, build your own.

John Jantsch (25:05.237)

Alright.

John Jantsch (25:21.632)

Yeah, yeah. Yeah, I’m curious. And again, you don’t have to answer this. can end on this. But I suspect that Google will build a cowork clone, you know, because you think of all the people have all of their stuff on Google Drive, and not just to be able to say, here, go consume all this. You’ve got to believe that’s coming. Well, Peter, I appreciate you.

Peter Benei (25:31.853)

Yeah.

Peter Benei (25:41.25)

Yes. And by the way, it’s interesting. Sorry, last sentence. I have to rant about Microsoft a little. It’s so interesting that you have all the documents on SharePoints and all the knowledge documents and stuff, and copilot is still. So it’s so weird. Anyway, sorry.

John Jantsch (25:46.794)

No, yeah, yeah.

Mm-hmm.

John Jantsch (26:01.909)

huh. Yeah. Yeah, yeah.

No, no, no, it has that typical Microsoft feel will land there. So Peter, I appreciate you taking a few moments to stop by. Is there some place you’d invite people to find out more about AI ready CMO?

Peter Benei (26:12.909)

Yeah.

Peter Benei (26:17.719)

Always.

Peter Benei (26:22.84)

Well, you just said it, AIReadyCMO.com. It’s free to subscribe. We share daily updates, daily intelligence. Every day it lands the one thing that you need to know about AI in marketing in your email box. Simple.

John Jantsch (26:25.954)

Yep, awesome.

John Jantsch (26:36.748)

Yeah, it is a newsletter that I read every day. appreciate it, All right, great. Well, appreciate you stopping by and hopefully maybe one of these days we’ll run into you on the road.

Peter Benei (26:42.476)

Thank you.

Peter Benei (26:50.358)

and anytime. Thank you very much for inviting me.

John Jantsch (26:51.797)

us.

John Jantsch (00:01.442)

Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch and my guest today is Peter Benei. He is a marketing leader and strategist with 20 plus years of experience as a CMO for tech scale-ups and startups. He co-founded AI Ready CMO, a platform and newsletter focused on helping marketing leaders adopt AI strategically, not just tool by tool, but through frameworks, case studies and community learning.

Peter Benei (00:01.57)

Thanks.

John Jantsch (00:30.39)

So guess what we’re going to talk about today? AI. Peter, welcome to the show.

Peter Benei (00:34.634)

Welcome and thanks for inviting me.

John Jantsch (00:38.028)

So given that you and I were just talking off air, you know, I’ve got 30 plus years, you’ve got 20 plus years, how in your mind has, does AI or the advent of AI different than say, websites and social media and search, you know, that kind of came along as tool? Would you say that it’s just another flavor or is it fundamentally different?

Peter Benei (00:43.341)

Yeah.

Peter Benei (01:04.052)

both, I guess. I had my own agency as well. Jesus, 20 years ago. and it was a social media agency. So at that time it was like, so Facebook business pages just got introduced and everyone was talking about the clue train manifesto markets are conversations and you know, this kind of stuff, social media, web two. I don’t know if you’re familiar with the market or Brian Solis.

John Jantsch (01:05.879)

Yeah.

John Jantsch (01:19.584)

Yeah.

John Jantsch (01:24.384)

Yeah. Yeah. Yeah. Yeah. Yeah.

Peter Benei (01:33.262)

Yeah, he was just about talking about the conversational prism and I don’t know. So everyone was talking about like, know, social media is a thing. And we had this agency, which was a social media agency. But again, that was a new thing. I don’t really think that the whole AI, whatever it is right now is…

John Jantsch (01:33.432)

Of course, yeah, Brian’s been on the show.

Peter Benei (02:02.4)

is new in a sense of tools and technology for marketers. These are just things that we need to learn and adapt to in general sense, like we did for, I don’t know, Facebook business pages at that time or, I don’t know, Squarespace websites. you can drag and drop websites again now. That’s interesting. Although I think the business model for agencies and marketing teams will be fundamentally changed

John Jantsch (02:22.53)

Yeah.

Peter Benei (02:32.184)

because of this new AI tool, AI capabilities, AI agent, whatever, AI. And I think that will be interesting to see. again, agencies also changed and marketing teams also changed 10, five, 20 years ago. So I think we just need to be familiar and open to adapt to this new change. So I don’t…

John Jantsch (03:00.31)

Well…

Peter Benei (03:01.078)

dramatize or strategize or panic around this. You just need to adapt.

John Jantsch (03:08.056)

Yeah, it’s funny. There was a period of time where you had social media marketing agencies and digital marketing agencies, right? It was just like, oh no, we’re this flavor. And now it’s just like, no, it’s all just marketing. Right. So what are the things you write about a lot? And, and I, you know, I’m a subscriber to your newsletter and I really, there are a lot of people out there writing about AI hype, you know, like look at what this thing could do. But I think you guys have take a very,

Peter Benei (03:12.206)

Hmm?

Peter Benei (03:19.693)

Yes.

Peter Benei (03:25.944)

Thank you.

John Jantsch (03:35.352)

Like you said, not necessarily a dramatic hype approach, a very almost stand back approach of saying, look, we have to remain strategic. Human beings have a role, but maybe it’s changed. And so I really appreciate that take. So let’s get in a little bit to the changing, like the AI plus strategy, you know, plus humans approach, because there’s certainly a lot of hand wringing right now around all these jobs that are going to be wiped out.

What are people going to do? So what do you, let’s just divide it. What do you think is going to go away that these tools actually do better than humans? And what do you think is going to actually stay and perhaps not for a long time be replaced by humans or by machines.

Peter Benei (04:05.486)

Thanks.

Peter Benei (04:21.922)

No, that’s a tempting and also interesting question. One thing that I want to reflect quickly, the focus on non-hype bullshit and sorry for calling that way, non-hype framing of this whole entire new trend was also personal choice of ours with the newsletter, but also a strategic choice as well.

Obviously everyone is hyping around this whole thing. we are personally, we are getting a little bit older, I guess. And we are just not interested in the, the, in the defocusing of our audiences. So we made the conscious decision to kind of like stand still and observe a little bit more with a strategic eye. So that’s one thing. Second.

John Jantsch (05:09.921)

Mm-hmm.

Peter Benei (05:18.232)

To your question, I would love to have an answer, but I’m not afraid to say that I don’t know. think during these times that are changing, it’s really hard to know what will happen. And we are just migrating, by the way, the news that are to another platform. And I had to reread the old stuff that we wrote. When I say old, like half a year ago.

John Jantsch (05:37.858)

Mm-hmm.

John Jantsch (05:47.832)

All right.

Peter Benei (05:48.174)

And that will be a context to your answer, by the way. And I just read what we’d wrote like half a year ago and everything was so beginning at that stage still. Everything changed so fast within a couple of months. New tools came out, new concepts introduced to the public. And I’m not talking about like agents, like more like, know.

John Jantsch (06:04.375)

Mm-hmm.

Peter Benei (06:14.818)

working together with AI, human in the loop, and these kind of stuff. It’s so hard to predict because within this small time frame, everything has changed. I think what we can do to answer this question, and sorry for it, it takes a little bit longer, is that to nail down the basics that we think that it will be changing. And I think there are a couple of things that will change. And one that I’m…

almost 100 % sure it will change is that production of marketing materials and like marketing production in a sense, like content production, shall we say, will be either fully automated or it will not come with a high barrier of entry. It doesn’t have a high barrier of entry right now either, but it will have like a minimum barrier of entry with AI.

John Jantsch (06:54.614)

Mm-hmm. Mm-hmm.

Peter Benei (07:14.254)

That means a lot for agencies, by the way, for marketing teams, because we create, mean, like 80 % of our work as marketers are creating content. Now, if the content creation is almost automated by AI, what do we do? Right? That’s the question. Now I don’t have the answer, but I’m sure that we won’t create that much and that amount of content within our workload and work time.

Second, AI is getting perfect or better, shall we say. It’s always, know, tomorrow’s AI is 10x better than today’s AI. But it’s still not perfect. And the reason why it’s not perfect is that it still needs the human, us, to course, supervise, review, edit, whatever. So I think the…

human in the loop or human in the addition working with the AI, it will matter for now, for a couple of years at least. And third, we need to think that if production is not our job anymore, but we still need it, then where do we need it? And I think that’s the answer for your question here, that we need to be able to form strategies.

And what is the strategy, by the way, understanding the client need with empathy and suggest process to achieve the goals. are goals and that’s it. Pretty much that’s the bare bones, simple strategy. How do we produce more? sorry. How do we produce better content? Because production wise, it will be automated, but it still has to be good. We need taste.

John Jantsch (08:56.45)

Right.

John Jantsch (09:09.698)

Right.

Peter Benei (09:11.106)

We need quality, we need judgment, we review supervision. And how do we work better with AI is that if we understand the workflows and the processes as a kind of like operator of the entire show. So I think strategy, like empathy, taste and operational efficiency or workflow knowledge should be…

and will be important for marketers. And I’m safe to say these.

John Jantsch (09:44.822)

Yeah, you, you. Well, and I think you raise a real, I think at least right now, one of the differentiators, the barrier to produce, to producing, quantity is gone. however, I think the barrier to producing quality is still a real differentiator.

Peter Benei (10:03.042)

Yeah. Yeah, I agree. agree. And it just, know, AI just like highlighted how not many of us have taste and how not many of us can produce great content and how most of the content that we’ve used so far anyway was, well, wouldn’t say garbage, but like, you know, mediocre. And I think it’s super important to…

to highlight that previously you needed resources to produce high quality content. So if you wanted to do a Super Bowl level advertising, you needed DDB or or or whoever big agency. If you wanted to do a global media campaign, you needed a media agency or an insane marketing budget to go with that.

John Jantsch (10:37.901)

Yes.

Peter Benei (11:02.638)

If you wanted to produce a content library of whatever you have, like 100 eBooks or shit, you need 10, 50, whatever, copywriters or marketers to do that. Similarly happening in other industries. So if you wanted to do the new John Wick movie, you needed a Hollywood studio and so on. can go on and on.

John Jantsch (11:18.338)

Thanks.

Peter Benei (11:33.184)

Now you don’t need these resources. You need a laptop and an idea and I don’t know, hundred dollars for API credits. And pretty much that’s it. That’s it. That’s all you need. And judgment and taste and strategic mindset. And, know, these kinds of stuff that are human in innate human values and abilities, which AI cannot produce.

John Jantsch (11:36.205)

Mm-hmm.

John Jantsch (12:02.658)

Well, so that begs the question then, if we are going to still have humans involved, do we need different humans? A lot of us. If we built an organization, say, to produce stuff, you know, the copywriters, the graphic designers, that their whole output was the stuff, do we now need to hire for taste and for judgment and for brand intuition?

Peter Benei (12:17.602)

Mm-hmm.

Peter Benei (12:27.83)

I yes. I’m not the person who will tell you otherwise. And I’m also not the person who is in the business who helps you to do that. But if I would be in the business, I would immediately start some sort of like a training company or anything around that that helps people who have like basic skills through studies. Like, I don’t know.

John Jantsch (12:28.92)

the

Peter Benei (12:57.806)

creative arts or whatever, and upgrading them to be able to use those skills in a refined manner for multiple purposes. In our case, marketing. So yeah, people and companies should hire Prudence.

John Jantsch (12:59.661)

Right.

John Jantsch (13:13.496)

And I think I’ve actually seen on your website, aren’t you producing some courses or some master classes or something around those? Yeah, yeah, okay.

Peter Benei (13:21.302)

Yeah, we do some workshops. We do some workshops, but we are not a training company. So, so we didn’t within AI ready CMO, if you like pave to go to get a paid member, you obviously have access to some sort of like a workshop training program and some studies, but we are not a training.

John Jantsch (13:26.551)

Yeah, yeah.

John Jantsch (13:40.994)

Right, right. Yeah, okay. So, would you… If somebody was, I don’t know, maybe coming out of school now or maybe trying to change careers or something, are there some roles or functions that you would say, hey, you should spend your time up-leveling your skills in this area?

Peter Benei (13:42.924)

And I don’t want to be a training company.

Peter Benei (13:52.334)

Hmm?

Peter Benei (14:03.608)

So I’m 44. That will be a long shot, I’m 44 and many of my friends have kids who are like 15 or 10 or 15 or 20 sometimes. And they all talk about the same thing. I like full honesty.

John Jantsch (14:30.84)

Mm-hmm.

Peter Benei (14:33.39)

They talk about what will these kids will do in five to 10 years, what kind of careers they will pursue and so on and so on. They are families. So I usually talk with the dads, obviously, and they are talking about, I need to send my kid to a university or college or whatever. I live in Europe, so I don’t know, they send it to Vienna or something. And how…

How should I pick which university they should go in and so on and so on? How should I help them? And they are clueless. And usually the close to good answer that I see, and again, this is a personal opinion, so treat it as is, usually the ones that are sending their kids to some sort of like art, history,

John Jantsch (15:10.776)

Mm-hmm.

Right.

John Jantsch (15:31.512)

Mm-hmm.

Peter Benei (15:32.782)

Literally something around these like soft things, which we call soft skills or soft studies.

John Jantsch (15:37.376)

Mm-hmm.

John Jantsch (15:41.495)

Mm-hmm.

Peter Benei (15:44.692)

I wouldn’t send my kid to engineering school right now. I wouldn’t send my kid to learn that become a developer or a lawyer or not even a doctor probably. I don’t think that these, I mean, these professions will exist obviously, but it will have a really huge competition that only the finest one will succeed or will be needed.

but if you have like a general arts degree or something around that, know usually, you know, treated as totally useless. I have one by the way. but still, so I studied history and sociology pretty much useless, I guess, but still. and I think these, these studies might be something that can be valuable because they, they teach you the basics of.

John Jantsch (16:22.922)

Right?

Peter Benei (16:43.64)

how to read, how to judge aesthetic things, and how to think critically, yes. How to think in context, so like historical context, let’s say. And I think these baseline knowledge skills, let’s say, I wouldn’t call them skills, but these things will be in, yes.

John Jantsch (16:49.89)

I to think critically.

John Jantsch (17:08.704)

It’s exposure really more than anything else, right? Yeah.

Peter Benei (17:11.746)

These will be inherently valuable than knowing the latest legal, whatever it is.

John Jantsch (17:14.274)

Yeah, yeah.

John Jantsch (17:19.308)

Yeah, yeah, yeah, which can be, yeah, queued up. How about CMOs? Are you, do you see that role going away? Do you see it, you know, changing inside of organizations to where it will not only look different, but it will have a different function?

Peter Benei (17:22.541)

Yes.

Peter Benei (17:38.232)

So we preach at AERA, the CMO is that the CMO role is becoming more like an orchestrator who is leading and creating these environments of workflows where people work together with AI and AI automation. And from the marketing org chart, like, know, junior, mid-manager, specialist.

John Jantsch (17:47.81)

Mm-hmm.

Peter Benei (18:07.128)

head off whatever and see. I do think that the CMO role will be the last one who will fall. Juniors probably will have the hardest time, especially, and also mid managers and specialists, because some of them need to pivot into something else because AI will just simply eat their field of expertise there.

but those people who are able to manage not just people, but workflows together. mixing the soft skills with, I wouldn’t say engineering level skills of workflow engineering, but more like, you know, operational level. I think these people will be valuable and these people will be the CMOs I think. But if you were a CMO and only created the marketing budget and.

John Jantsch (18:53.516)

Mm-hmm.

Peter Benei (19:06.306)

delegated the tasks and that’s it. Yeah, you probably will have a harder time in the upcoming years and you need to learn workflow efficiency, operational level execute and you know, these kinds of Or if you are on the other side, more like an operational person, you probably need to learn a little bit more soft skills and judgment and taste and you know, these kinds of stuff that we talked about so far.

John Jantsch (19:35.124)

So I want end on one kind of, there’s a bit of been a bit of a rant for me and I’m curious where you land on this. I think a lot of people were jumping at, my AI tool stack is these 17 tools because they all do one thing really well. And I think what I’ve said all along is I think the Googles and the Microsofts of the world are going to basically figure out how to build all of those best of class tools into their

Peter Benei (19:41.774)

Please.

Peter Benei (19:51.342)

Hmm.

Peter Benei (20:03.448)

Agree.

John Jantsch (20:04.696)

into their work tool that you buy for one price or that you’re already buying that now is just $10 more a month. And they will really kind of wipe out a lot of these one-off tools. I’m curious what you think of that.

Peter Benei (20:10.926)

I agree.

Peter Benei (20:18.094)

100%. I mean, this will be a hard argument because I 100 % agree with you. I can share you two examples. Two examples and one explanation on why people think that. I mean, especially, know, C level people and decision makers, they love throwing resources on problems. So yeah, they have like a tool.

John Jantsch (20:43.352)

Mm-hmm.

Peter Benei (20:48.174)

abundance, and they, and they buy shiny new tools every day. that’s fine. We understand it’s obviously not the right call. and even, even they don’t, they know it usually. and the two examples are, are simple ones. One, you actually mentioned off of air that you read the latest article that we, that we published. I mean, it’s not rocket science judge, just a Claude Cowork, came out.

John Jantsch (21:16.941)

Yes.

Peter Benei (21:18.282)

A funny thing, by the way, did Claude did it. mean, the Anthropic team did it with Claude code within half, one and a half a week. And no line of code were written by any engineers, all AI. So the learning there is that most of the tools will be irrelevant because startups

John Jantsch (21:29.848)

Mm.

John Jantsch (21:34.934)

Yes.

Peter Benei (21:45.674)

And AI tools just die every day because new tools will come out. Also don’t forget that the big ones, Google and the others, they have infinite resources, like infinite. They have infinite training data and AI lives on data. So just like one simple AI feature added to Google ads, let’s say.

We’ll probably kill 90 % of the AI tools out there right now overnight.

John Jantsch (22:20.972)

Well, they also, know, one thing people underestimate, they also have all the hardware.

Peter Benei (22:25.216)

And also the hardware. Well, in a sense business, that hardware doesn’t really matter that much, more like the data, but yeah, the hardware is important too. And the second thing is that, well, I’m really proud of it because it happened today. So sorry for sharing it with everyone right now on this podcast, but I built a content repurposing application. You literally, it does…

John Jantsch (22:26.584)

So it doesn’t cost them anything.

John Jantsch (22:35.49)

Yeah. Yeah.

John Jantsch (22:45.208)

You

Peter Benei (22:54.956)

A simple thing, you give an RSS feed to the application, in our case, our newsletter. We are only two people. So we don’t have social media managers and stuff. And because most of the content that we do is news-driven, so every day we publish something new. We cannot batch write stuff pre-time. So we only know the content on the same day.

and we need to share it on X and everywhere. And we spend a lot of time to repurposing this type of content, even if we use AI. So this app actually takes everything that we have, new posts, and repurpose it on different platforms. It self-learns, it does everything. It’s fully automated, it’s amazing. It has a UX, everything.

and I built it under an hour while I having breakfast at my kitchen table. I’m not kidding. And I don’t know how to code at all. Like I never coded a single line of code ever. And I will probably never will. Claude did it. just why prompting it. So the reason why I’m telling this, thing is that it’s so easy to build up something new now.

John Jantsch (23:58.336)

Yeah.

Peter Benei (24:21.134)

even for personal use that you probably end up and that’s like a wild guess and more like a futurism. But I might guess that within a year or two, we don’t really even have like small sasses for most companies. People just, you know, ramp up their own applications for their own computer, for their own personal use, for their own agency, for their own clients within an hour.

John Jantsch (24:21.186)

Yeah. Right.

Peter Benei (24:50.508)

works fine just for them.

John Jantsch (24:53.016)

Yes. Yes, yes.

Peter Benei (24:54.382)

So it’s interesting. So short answer to your question. mean, don’t really bother subscribing to 20-something AI tools. Probably 95 % of them will be extinct within a year or two and substitute by Gemini or other Google products or whatever. Or second answer, build your own.

John Jantsch (25:05.237)

Alright.

John Jantsch (25:21.632)

Yeah, yeah. Yeah, I’m curious. And again, you don’t have to answer this. can end on this. But I suspect that Google will build a cowork clone, you know, because you think of all the people have all of their stuff on Google Drive, and not just to be able to say, here, go consume all this. You’ve got to believe that’s coming. Well, Peter, I appreciate you.

Peter Benei (25:31.853)

Yeah.

Peter Benei (25:41.25)

Yes. And by the way, it’s interesting. Sorry, last sentence. I have to rant about Microsoft a little. It’s so interesting that you have all the documents on SharePoints and all the knowledge documents and stuff, and copilot is still. So it’s so weird. Anyway, sorry.

John Jantsch (25:46.794)

No, yeah, yeah.

Mm-hmm.

John Jantsch (26:01.909)

huh. Yeah. Yeah, yeah.

No, no, no, it has that typical Microsoft feel will land there. So Peter, I appreciate you taking a few moments to stop by. Is there some place you’d invite people to find out more about AI ready CMO?

Peter Benei (26:12.909)

Yeah.

Peter Benei (26:17.719)

Always.

Peter Benei (26:22.84)

Well, you just said it, AIReadyCMO.com. It’s free to subscribe. We share daily updates, daily intelligence. Every day it lands the one thing that you need to know about AI in marketing in your email box. Simple.

John Jantsch (26:25.954)

Yep, awesome.

John Jantsch (26:36.748)

Yeah, it is a newsletter that I read every day. appreciate it, All right, great. Well, appreciate you stopping by and hopefully maybe one of these days we’ll run into you on the road.

Peter Benei (26:42.476)

Thank you.

Peter Benei (26:50.358)

and anytime. Thank you very much for inviting me.

John Jantsch (26:51.797)

us.

John Jantsch (00:01.442)

Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch and my guest today is Peter Benei. He is a marketing leader and strategist with 20 plus years of experience as a CMO for tech scale-ups and startups. He co-founded AI Ready CMO, a platform and newsletter focused on helping marketing leaders adopt AI strategically, not just tool by tool, but through frameworks, case studies and community learning.

Peter Benei (00:01.57)

Thanks.

John Jantsch (00:30.39)

So guess what we’re going to talk about today? AI. Peter, welcome to the show.

Peter Benei (00:34.634)

Welcome and thanks for inviting me.

John Jantsch (00:38.028)

So given that you and I were just talking off air, you know, I’ve got 30 plus years, you’ve got 20 plus years, how in your mind has, does AI or the advent of AI different than say, websites and social media and search, you know, that kind of came along as tool? Would you say that it’s just another flavor or is it fundamentally different?

Peter Benei (00:43.341)

Yeah.

Peter Benei (01:04.052)

both, I guess. I had my own agency as well. Jesus, 20 years ago. and it was a social media agency. So at that time it was like, so Facebook business pages just got introduced and everyone was talking about the clue train manifesto markets are conversations and you know, this kind of stuff, social media, web two. I don’t know if you’re familiar with the market or Brian Solis.

John Jantsch (01:05.879)

Yeah.

John Jantsch (01:19.584)

Yeah.

John Jantsch (01:24.384)

Yeah. Yeah. Yeah. Yeah. Yeah.

Peter Benei (01:33.262)

Yeah, he was just about talking about the conversational prism and I don’t know. So everyone was talking about like, know, social media is a thing. And we had this agency, which was a social media agency. But again, that was a new thing. I don’t really think that the whole AI, whatever it is right now is…

John Jantsch (01:33.432)

Of course, yeah, Brian’s been on the show.

Peter Benei (02:02.4)

is new in a sense of tools and technology for marketers. These are just things that we need to learn and adapt to in general sense, like we did for, I don’t know, Facebook business pages at that time or, I don’t know, Squarespace websites. you can drag and drop websites again now. That’s interesting. Although I think the business model for agencies and marketing teams will be fundamentally changed

John Jantsch (02:22.53)

Yeah.

Peter Benei (02:32.184)

because of this new AI tool, AI capabilities, AI agent, whatever, AI. And I think that will be interesting to see. again, agencies also changed and marketing teams also changed 10, five, 20 years ago. So I think we just need to be familiar and open to adapt to this new change. So I don’t…

John Jantsch (03:00.31)

Well…

Peter Benei (03:01.078)

dramatize or strategize or panic around this. You just need to adapt.

John Jantsch (03:08.056)

Yeah, it’s funny. There was a period of time where you had social media marketing agencies and digital marketing agencies, right? It was just like, oh no, we’re this flavor. And now it’s just like, no, it’s all just marketing. Right. So what are the things you write about a lot? And, and I, you know, I’m a subscriber to your newsletter and I really, there are a lot of people out there writing about AI hype, you know, like look at what this thing could do. But I think you guys have take a very,

Peter Benei (03:12.206)

Hmm?

Peter Benei (03:19.693)

Yes.

Peter Benei (03:25.944)

Thank you.

John Jantsch (03:35.352)

Like you said, not necessarily a dramatic hype approach, a very almost stand back approach of saying, look, we have to remain strategic. Human beings have a role, but maybe it’s changed. And so I really appreciate that take. So let’s get in a little bit to the changing, like the AI plus strategy, you know, plus humans approach, because there’s certainly a lot of hand wringing right now around all these jobs that are going to be wiped out.

What are people going to do? So what do you, let’s just divide it. What do you think is going to go away that these tools actually do better than humans? And what do you think is going to actually stay and perhaps not for a long time be replaced by humans or by machines.

Peter Benei (04:05.486)

Thanks.

Peter Benei (04:21.922)

No, that’s a tempting and also interesting question. One thing that I want to reflect quickly, the focus on non-hype bullshit and sorry for calling that way, non-hype framing of this whole entire new trend was also personal choice of ours with the newsletter, but also a strategic choice as well.

Obviously everyone is hyping around this whole thing. we are personally, we are getting a little bit older, I guess. And we are just not interested in the, the, in the defocusing of our audiences. So we made the conscious decision to kind of like stand still and observe a little bit more with a strategic eye. So that’s one thing. Second.

John Jantsch (05:09.921)

Mm-hmm.

Peter Benei (05:18.232)

To your question, I would love to have an answer, but I’m not afraid to say that I don’t know. think during these times that are changing, it’s really hard to know what will happen. And we are just migrating, by the way, the news that are to another platform. And I had to reread the old stuff that we wrote. When I say old, like half a year ago.

John Jantsch (05:37.858)

Mm-hmm.

John Jantsch (05:47.832)

All right.

Peter Benei (05:48.174)

And that will be a context to your answer, by the way. And I just read what we’d wrote like half a year ago and everything was so beginning at that stage still. Everything changed so fast within a couple of months. New tools came out, new concepts introduced to the public. And I’m not talking about like agents, like more like, know.

John Jantsch (06:04.375)

Mm-hmm.

Peter Benei (06:14.818)

working together with AI, human in the loop, and these kind of stuff. It’s so hard to predict because within this small time frame, everything has changed. I think what we can do to answer this question, and sorry for it, it takes a little bit longer, is that to nail down the basics that we think that it will be changing. And I think there are a couple of things that will change. And one that I’m…

almost 100 % sure it will change is that production of marketing materials and like marketing production in a sense, like content production, shall we say, will be either fully automated or it will not come with a high barrier of entry. It doesn’t have a high barrier of entry right now either, but it will have like a minimum barrier of entry with AI.

John Jantsch (06:54.614)

Mm-hmm. Mm-hmm.

Peter Benei (07:14.254)

That means a lot for agencies, by the way, for marketing teams, because we create, mean, like 80 % of our work as marketers are creating content. Now, if the content creation is almost automated by AI, what do we do? Right? That’s the question. Now I don’t have the answer, but I’m sure that we won’t create that much and that amount of content within our workload and work time.

Second, AI is getting perfect or better, shall we say. It’s always, know, tomorrow’s AI is 10x better than today’s AI. But it’s still not perfect. And the reason why it’s not perfect is that it still needs the human, us, to course, supervise, review, edit, whatever. So I think the…

human in the loop or human in the addition working with the AI, it will matter for now, for a couple of years at least. And third, we need to think that if production is not our job anymore, but we still need it, then where do we need it? And I think that’s the answer for your question here, that we need to be able to form strategies.

And what is the strategy, by the way, understanding the client need with empathy and suggest process to achieve the goals. are goals and that’s it. Pretty much that’s the bare bones, simple strategy. How do we produce more? sorry. How do we produce better content? Because production wise, it will be automated, but it still has to be good. We need taste.

John Jantsch (08:56.45)

Right.

John Jantsch (09:09.698)

Right.

Peter Benei (09:11.106)

We need quality, we need judgment, we review supervision. And how do we work better with AI is that if we understand the workflows and the processes as a kind of like operator of the entire show. So I think strategy, like empathy, taste and operational efficiency or workflow knowledge should be…

and will be important for marketers. And I’m safe to say these.

John Jantsch (09:44.822)

Yeah, you, you. Well, and I think you raise a real, I think at least right now, one of the differentiators, the barrier to produce, to producing, quantity is gone. however, I think the barrier to producing quality is still a real differentiator.

Peter Benei (10:03.042)

Yeah. Yeah, I agree. agree. And it just, know, AI just like highlighted how not many of us have taste and how not many of us can produce great content and how most of the content that we’ve used so far anyway was, well, wouldn’t say garbage, but like, you know, mediocre. And I think it’s super important to…

to highlight that previously you needed resources to produce high quality content. So if you wanted to do a Super Bowl level advertising, you needed DDB or or or whoever big agency. If you wanted to do a global media campaign, you needed a media agency or an insane marketing budget to go with that.

John Jantsch (10:37.901)

Yes.

Peter Benei (11:02.638)

If you wanted to produce a content library of whatever you have, like 100 eBooks or shit, you need 10, 50, whatever, copywriters or marketers to do that. Similarly happening in other industries. So if you wanted to do the new John Wick movie, you needed a Hollywood studio and so on. can go on and on.

John Jantsch (11:18.338)

Thanks.

Peter Benei (11:33.184)

Now you don’t need these resources. You need a laptop and an idea and I don’t know, hundred dollars for API credits. And pretty much that’s it. That’s it. That’s all you need. And judgment and taste and strategic mindset. And, know, these kinds of stuff that are human in innate human values and abilities, which AI cannot produce.

John Jantsch (11:36.205)

Mm-hmm.

John Jantsch (12:02.658)

Well, so that begs the question then, if we are going to still have humans involved, do we need different humans? A lot of us. If we built an organization, say, to produce stuff, you know, the copywriters, the graphic designers, that their whole output was the stuff, do we now need to hire for taste and for judgment and for brand intuition?

Peter Benei (12:17.602)

Mm-hmm.

Peter Benei (12:27.83)

I yes. I’m not the person who will tell you otherwise. And I’m also not the person who is in the business who helps you to do that. But if I would be in the business, I would immediately start some sort of like a training company or anything around that that helps people who have like basic skills through studies. Like, I don’t know.

John Jantsch (12:28.92)

the

Peter Benei (12:57.806)

creative arts or whatever, and upgrading them to be able to use those skills in a refined manner for multiple purposes. In our case, marketing. So yeah, people and companies should hire Prudence.

John Jantsch (12:59.661)

Right.

John Jantsch (13:13.496)

And I think I’ve actually seen on your website, aren’t you producing some courses or some master classes or something around those? Yeah, yeah, okay.

Peter Benei (13:21.302)

Yeah, we do some workshops. We do some workshops, but we are not a training company. So, so we didn’t within AI ready CMO, if you like pave to go to get a paid member, you obviously have access to some sort of like a workshop training program and some studies, but we are not a training.

John Jantsch (13:26.551)

Yeah, yeah.

John Jantsch (13:40.994)

Right, right. Yeah, okay. So, would you… If somebody was, I don’t know, maybe coming out of school now or maybe trying to change careers or something, are there some roles or functions that you would say, hey, you should spend your time up-leveling your skills in this area?

Peter Benei (13:42.924)

And I don’t want to be a training company.

Peter Benei (13:52.334)

Hmm?

Peter Benei (14:03.608)

So I’m 44. That will be a long shot, I’m 44 and many of my friends have kids who are like 15 or 10 or 15 or 20 sometimes. And they all talk about the same thing. I like full honesty.

John Jantsch (14:30.84)

Mm-hmm.

Peter Benei (14:33.39)

They talk about what will these kids will do in five to 10 years, what kind of careers they will pursue and so on and so on. They are families. So I usually talk with the dads, obviously, and they are talking about, I need to send my kid to a university or college or whatever. I live in Europe, so I don’t know, they send it to Vienna or something. And how…

How should I pick which university they should go in and so on and so on? How should I help them? And they are clueless. And usually the close to good answer that I see, and again, this is a personal opinion, so treat it as is, usually the ones that are sending their kids to some sort of like art, history,

John Jantsch (15:10.776)

Mm-hmm.

Right.

John Jantsch (15:31.512)

Mm-hmm.

Peter Benei (15:32.782)

Literally something around these like soft things, which we call soft skills or soft studies.

John Jantsch (15:37.376)

Mm-hmm.

John Jantsch (15:41.495)

Mm-hmm.

Peter Benei (15:44.692)

I wouldn’t send my kid to engineering school right now. I wouldn’t send my kid to learn that become a developer or a lawyer or not even a doctor probably. I don’t think that these, I mean, these professions will exist obviously, but it will have a really huge competition that only the finest one will succeed or will be needed.

but if you have like a general arts degree or something around that, know usually, you know, treated as totally useless. I have one by the way. but still, so I studied history and sociology pretty much useless, I guess, but still. and I think these, these studies might be something that can be valuable because they, they teach you the basics of.

John Jantsch (16:22.922)

Right?

Peter Benei (16:43.64)

how to read, how to judge aesthetic things, and how to think critically, yes. How to think in context, so like historical context, let’s say. And I think these baseline knowledge skills, let’s say, I wouldn’t call them skills, but these things will be in, yes.

John Jantsch (16:49.89)

I to think critically.

John Jantsch (17:08.704)

It’s exposure really more than anything else, right? Yeah.

Peter Benei (17:11.746)

These will be inherently valuable than knowing the latest legal, whatever it is.

John Jantsch (17:14.274)

Yeah, yeah.

John Jantsch (17:19.308)

Yeah, yeah, yeah, which can be, yeah, queued up. How about CMOs? Are you, do you see that role going away? Do you see it, you know, changing inside of organizations to where it will not only look different, but it will have a different function?

Peter Benei (17:22.541)

Yes.

Peter Benei (17:38.232)

So we preach at AERA, the CMO is that the CMO role is becoming more like an orchestrator who is leading and creating these environments of workflows where people work together with AI and AI automation. And from the marketing org chart, like, know, junior, mid-manager, specialist.

John Jantsch (17:47.81)

Mm-hmm.

Peter Benei (18:07.128)

head off whatever and see. I do think that the CMO role will be the last one who will fall. Juniors probably will have the hardest time, especially, and also mid managers and specialists, because some of them need to pivot into something else because AI will just simply eat their field of expertise there.

but those people who are able to manage not just people, but workflows together. mixing the soft skills with, I wouldn’t say engineering level skills of workflow engineering, but more like, you know, operational level. I think these people will be valuable and these people will be the CMOs I think. But if you were a CMO and only created the marketing budget and.

John Jantsch (18:53.516)

Mm-hmm.

Peter Benei (19:06.306)

delegated the tasks and that’s it. Yeah, you probably will have a harder time in the upcoming years and you need to learn workflow efficiency, operational level execute and you know, these kinds of Or if you are on the other side, more like an operational person, you probably need to learn a little bit more soft skills and judgment and taste and you know, these kinds of stuff that we talked about so far.

John Jantsch (19:35.124)

So I want end on one kind of, there’s a bit of been a bit of a rant for me and I’m curious where you land on this. I think a lot of people were jumping at, my AI tool stack is these 17 tools because they all do one thing really well. And I think what I’ve said all along is I think the Googles and the Microsofts of the world are going to basically figure out how to build all of those best of class tools into their

Peter Benei (19:41.774)

Please.

Peter Benei (19:51.342)

Hmm.

Peter Benei (20:03.448)

Agree.

John Jantsch (20:04.696)

into their work tool that you buy for one price or that you’re already buying that now is just $10 more a month. And they will really kind of wipe out a lot of these one-off tools. I’m curious what you think of that.

Peter Benei (20:10.926)

I agree.

Peter Benei (20:18.094)

100%. I mean, this will be a hard argument because I 100 % agree with you. I can share you two examples. Two examples and one explanation on why people think that. I mean, especially, know, C level people and decision makers, they love throwing resources on problems. So yeah, they have like a tool.

John Jantsch (20:43.352)

Mm-hmm.

Peter Benei (20:48.174)

abundance, and they, and they buy shiny new tools every day. that’s fine. We understand it’s obviously not the right call. and even, even they don’t, they know it usually. and the two examples are, are simple ones. One, you actually mentioned off of air that you read the latest article that we, that we published. I mean, it’s not rocket science judge, just a Claude Cowork, came out.

John Jantsch (21:16.941)

Yes.

Peter Benei (21:18.282)

A funny thing, by the way, did Claude did it. mean, the Anthropic team did it with Claude code within half, one and a half a week. And no line of code were written by any engineers, all AI. So the learning there is that most of the tools will be irrelevant because startups

John Jantsch (21:29.848)

Mm.

John Jantsch (21:34.934)

Yes.

Peter Benei (21:45.674)

And AI tools just die every day because new tools will come out. Also don’t forget that the big ones, Google and the others, they have infinite resources, like infinite. They have infinite training data and AI lives on data. So just like one simple AI feature added to Google ads, let’s say.

We’ll probably kill 90 % of the AI tools out there right now overnight.

John Jantsch (22:20.972)

Well, they also, know, one thing people underestimate, they also have all the hardware.

Peter Benei (22:25.216)

And also the hardware. Well, in a sense business, that hardware doesn’t really matter that much, more like the data, but yeah, the hardware is important too. And the second thing is that, well, I’m really proud of it because it happened today. So sorry for sharing it with everyone right now on this podcast, but I built a content repurposing application. You literally, it does…

John Jantsch (22:26.584)

So it doesn’t cost them anything.

John Jantsch (22:35.49)

Yeah. Yeah.

John Jantsch (22:45.208)

You

Peter Benei (22:54.956)

A simple thing, you give an RSS feed to the application, in our case, our newsletter. We are only two people. So we don’t have social media managers and stuff. And because most of the content that we do is news-driven, so every day we publish something new. We cannot batch write stuff pre-time. So we only know the content on the same day.

and we need to share it on X and everywhere. And we spend a lot of time to repurposing this type of content, even if we use AI. So this app actually takes everything that we have, new posts, and repurpose it on different platforms. It self-learns, it does everything. It’s fully automated, it’s amazing. It has a UX, everything.

and I built it under an hour while I having breakfast at my kitchen table. I’m not kidding. And I don’t know how to code at all. Like I never coded a single line of code ever. And I will probably never will. Claude did it. just why prompting it. So the reason why I’m telling this, thing is that it’s so easy to build up something new now.

John Jantsch (23:58.336)

Yeah.

Peter Benei (24:21.134)

even for personal use that you probably end up and that’s like a wild guess and more like a futurism. But I might guess that within a year or two, we don’t really even have like small sasses for most companies. People just, you know, ramp up their own applications for their own computer, for their own personal use, for their own agency, for their own clients within an hour.

John Jantsch (24:21.186)

Yeah. Right.

Peter Benei (24:50.508)

works fine just for them.

John Jantsch (24:53.016)

Yes. Yes, yes.

Peter Benei (24:54.382)

So it’s interesting. So short answer to your question. mean, don’t really bother subscribing to 20-something AI tools. Probably 95 % of them will be extinct within a year or two and substitute by Gemini or other Google products or whatever. Or second answer, build your own.

John Jantsch (25:05.237)

Alright.

John Jantsch (25:21.632)

Yeah, yeah. Yeah, I’m curious. And again, you don’t have to answer this. can end on this. But I suspect that Google will build a cowork clone, you know, because you think of all the people have all of their stuff on Google Drive, and not just to be able to say, here, go consume all this. You’ve got to believe that’s coming. Well, Peter, I appreciate you.

Peter Benei (25:31.853)

Yeah.

Peter Benei (25:41.25)

Yes. And by the way, it’s interesting. Sorry, last sentence. I have to rant about Microsoft a little. It’s so interesting that you have all the documents on SharePoints and all the knowledge documents and stuff, and copilot is still. So it’s so weird. Anyway, sorry.

John Jantsch (25:46.794)

No, yeah, yeah.

Mm-hmm.

John Jantsch (26:01.909)

huh. Yeah. Yeah, yeah.

No, no, no, it has that typical Microsoft feel will land there. So Peter, I appreciate you taking a few moments to stop by. Is there some place you’d invite people to find out more about AI ready CMO?

Peter Benei (26:12.909)

Yeah.

Peter Benei (26:17.719)

Always.

Peter Benei (26:22.84)

Well, you just said it, AIReadyCMO.com. It’s free to subscribe. We share daily updates, daily intelligence. Every day it lands the one thing that you need to know about AI in marketing in your email box. Simple.

John Jantsch (26:25.954)

Yep, awesome.

John Jantsch (26:36.748)

Yeah, it is a newsletter that I read every day. appreciate it, All right, great. Well, appreciate you stopping by and hopefully maybe one of these days we’ll run into you on the road.

Peter Benei (26:42.476)

Thank you.

Peter Benei (26:50.358)

and anytime. Thank you very much for inviting me.

John Jantsch (26:51.797)

us.

John Jantsch (00:01.442)

Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch and my guest today is Peter Benei. He is a marketing leader and strategist with 20 plus years of experience as a CMO for tech scale-ups and startups. He co-founded AI Ready CMO, a platform and newsletter focused on helping marketing leaders adopt AI strategically, not just tool by tool, but through frameworks, case studies and community learning.

Peter Benei (00:01.57)

Thanks.

John Jantsch (00:30.39)

So guess what we’re going to talk about today? AI. Peter, welcome to the show.

Peter Benei (00:34.634)

Welcome and thanks for inviting me.

John Jantsch (00:38.028)

So given that you and I were just talking off air, you know, I’ve got 30 plus years, you’ve got 20 plus years, how in your mind has, does AI or the advent of AI different than say, websites and social media and search, you know, that kind of came along as tool? Would you say that it’s just another flavor or is it fundamentally different?

Peter Benei (00:43.341)

Yeah.

Peter Benei (01:04.052)

both, I guess. I had my own agency as well. Jesus, 20 years ago. and it was a social media agency. So at that time it was like, so Facebook business pages just got introduced and everyone was talking about the clue train manifesto markets are conversations and you know, this kind of stuff, social media, web two. I don’t know if you’re familiar with the market or Brian Solis.

John Jantsch (01:05.879)

Yeah.

John Jantsch (01:19.584)

Yeah.

John Jantsch (01:24.384)

Yeah. Yeah. Yeah. Yeah. Yeah.

Peter Benei (01:33.262)

Yeah, he was just about talking about the conversational prism and I don’t know. So everyone was talking about like, know, social media is a thing. And we had this agency, which was a social media agency. But again, that was a new thing. I don’t really think that the whole AI, whatever it is right now is…

John Jantsch (01:33.432)

Of course, yeah, Brian’s been on the show.

Peter Benei (02:02.4)

is new in a sense of tools and technology for marketers. These are just things that we need to learn and adapt to in general sense, like we did for, I don’t know, Facebook business pages at that time or, I don’t know, Squarespace websites. you can drag and drop websites again now. That’s interesting. Although I think the business model for agencies and marketing teams will be fundamentally changed

John Jantsch (02:22.53)

Yeah.

Peter Benei (02:32.184)

because of this new AI tool, AI capabilities, AI agent, whatever, AI. And I think that will be interesting to see. again, agencies also changed and marketing teams also changed 10, five, 20 years ago. So I think we just need to be familiar and open to adapt to this new change. So I don’t…

John Jantsch (03:00.31)

Well…

Peter Benei (03:01.078)

dramatize or strategize or panic around this. You just need to adapt.

John Jantsch (03:08.056)

Yeah, it’s funny. There was a period of time where you had social media marketing agencies and digital marketing agencies, right? It was just like, oh no, we’re this flavor. And now it’s just like, no, it’s all just marketing. Right. So what are the things you write about a lot? And, and I, you know, I’m a subscriber to your newsletter and I really, there are a lot of people out there writing about AI hype, you know, like look at what this thing could do. But I think you guys have take a very,

Peter Benei (03:12.206)

Hmm?

Peter Benei (03:19.693)

Yes.

Peter Benei (03:25.944)

Thank you.

John Jantsch (03:35.352)

Like you said, not necessarily a dramatic hype approach, a very almost stand back approach of saying, look, we have to remain strategic. Human beings have a role, but maybe it’s changed. And so I really appreciate that take. So let’s get in a little bit to the changing, like the AI plus strategy, you know, plus humans approach, because there’s certainly a lot of hand wringing right now around all these jobs that are going to be wiped out.

What are people going to do? So what do you, let’s just divide it. What do you think is going to go away that these tools actually do better than humans? And what do you think is going to actually stay and perhaps not for a long time be replaced by humans or by machines.

Peter Benei (04:05.486)

Thanks.

Peter Benei (04:21.922)

No, that’s a tempting and also interesting question. One thing that I want to reflect quickly, the focus on non-hype bullshit and sorry for calling that way, non-hype framing of this whole entire new trend was also personal choice of ours with the newsletter, but also a strategic choice as well.

Obviously everyone is hyping around this whole thing. we are personally, we are getting a little bit older, I guess. And we are just not interested in the, the, in the defocusing of our audiences. So we made the conscious decision to kind of like stand still and observe a little bit more with a strategic eye. So that’s one thing. Second.

John Jantsch (05:09.921)

Mm-hmm.

Peter Benei (05:18.232)

To your question, I would love to have an answer, but I’m not afraid to say that I don’t know. think during these times that are changing, it’s really hard to know what will happen. And we are just migrating, by the way, the news that are to another platform. And I had to reread the old stuff that we wrote. When I say old, like half a year ago.

John Jantsch (05:37.858)

Mm-hmm.

John Jantsch (05:47.832)

All right.

Peter Benei (05:48.174)

And that will be a context to your answer, by the way. And I just read what we’d wrote like half a year ago and everything was so beginning at that stage still. Everything changed so fast within a couple of months. New tools came out, new concepts introduced to the public. And I’m not talking about like agents, like more like, know.

John Jantsch (06:04.375)

Mm-hmm.

Peter Benei (06:14.818)

working together with AI, human in the loop, and these kind of stuff. It’s so hard to predict because within this small time frame, everything has changed. I think what we can do to answer this question, and sorry for it, it takes a little bit longer, is that to nail down the basics that we think that it will be changing. And I think there are a couple of things that will change. And one that I’m…

almost 100 % sure it will change is that production of marketing materials and like marketing production in a sense, like content production, shall we say, will be either fully automated or it will not come with a high barrier of entry. It doesn’t have a high barrier of entry right now either, but it will have like a minimum barrier of entry with AI.

John Jantsch (06:54.614)

Mm-hmm. Mm-hmm.

Peter Benei (07:14.254)

That means a lot for agencies, by the way, for marketing teams, because we create, mean, like 80 % of our work as marketers are creating content. Now, if the content creation is almost automated by AI, what do we do? Right? That’s the question. Now I don’t have the answer, but I’m sure that we won’t create that much and that amount of content within our workload and work time.

Second, AI is getting perfect or better, shall we say. It’s always, know, tomorrow’s AI is 10x better than today’s AI. But it’s still not perfect. And the reason why it’s not perfect is that it still needs the human, us, to course, supervise, review, edit, whatever. So I think the…

human in the loop or human in the addition working with the AI, it will matter for now, for a couple of years at least. And third, we need to think that if production is not our job anymore, but we still need it, then where do we need it? And I think that’s the answer for your question here, that we need to be able to form strategies.

And what is the strategy, by the way, understanding the client need with empathy and suggest process to achieve the goals. are goals and that’s it. Pretty much that’s the bare bones, simple strategy. How do we produce more? sorry. How do we produce better content? Because production wise, it will be automated, but it still has to be good. We need taste.

John Jantsch (08:56.45)

Right.

John Jantsch (09:09.698)

Right.

Peter Benei (09:11.106)

We need quality, we need judgment, we review supervision. And how do we work better with AI is that if we understand the workflows and the processes as a kind of like operator of the entire show. So I think strategy, like empathy, taste and operational efficiency or workflow knowledge should be…

and will be important for marketers. And I’m safe to say these.

John Jantsch (09:44.822)

Yeah, you, you. Well, and I think you raise a real, I think at least right now, one of the differentiators, the barrier to produce, to producing, quantity is gone. however, I think the barrier to producing quality is still a real differentiator.

Peter Benei (10:03.042)

Yeah. Yeah, I agree. agree. And it just, know, AI just like highlighted how not many of us have taste and how not many of us can produce great content and how most of the content that we’ve used so far anyway was, well, wouldn’t say garbage, but like, you know, mediocre. And I think it’s super important to…

to highlight that previously you needed resources to produce high quality content. So if you wanted to do a Super Bowl level advertising, you needed DDB or or or whoever big agency. If you wanted to do a global media campaign, you needed a media agency or an insane marketing budget to go with that.

John Jantsch (10:37.901)

Yes.

Peter Benei (11:02.638)

If you wanted to produce a content library of whatever you have, like 100 eBooks or shit, you need 10, 50, whatever, copywriters or marketers to do that. Similarly happening in other industries. So if you wanted to do the new John Wick movie, you needed a Hollywood studio and so on. can go on and on.

John Jantsch (11:18.338)

Thanks.

Peter Benei (11:33.184)

Now you don’t need these resources. You need a laptop and an idea and I don’t know, hundred dollars for API credits. And pretty much that’s it. That’s it. That’s all you need. And judgment and taste and strategic mindset. And, know, these kinds of stuff that are human in innate human values and abilities, which AI cannot produce.

John Jantsch (11:36.205)

Mm-hmm.

John Jantsch (12:02.658)

Well, so that begs the question then, if we are going to still have humans involved, do we need different humans? A lot of us. If we built an organization, say, to produce stuff, you know, the copywriters, the graphic designers, that their whole output was the stuff, do we now need to hire for taste and for judgment and for brand intuition?

Peter Benei (12:17.602)

Mm-hmm.

Peter Benei (12:27.83)

I yes. I’m not the person who will tell you otherwise. And I’m also not the person who is in the business who helps you to do that. But if I would be in the business, I would immediately start some sort of like a training company or anything around that that helps people who have like basic skills through studies. Like, I don’t know.

John Jantsch (12:28.92)

the

Peter Benei (12:57.806)

creative arts or whatever, and upgrading them to be able to use those skills in a refined manner for multiple purposes. In our case, marketing. So yeah, people and companies should hire Prudence.

John Jantsch (12:59.661)

Right.

John Jantsch (13:13.496)

And I think I’ve actually seen on your website, aren’t you producing some courses or some master classes or something around those? Yeah, yeah, okay.

Peter Benei (13:21.302)

Yeah, we do some workshops. We do some workshops, but we are not a training company. So, so we didn’t within AI ready CMO, if you like pave to go to get a paid member, you obviously have access to some sort of like a workshop training program and some studies, but we are not a training.

John Jantsch (13:26.551)

Yeah, yeah.

John Jantsch (13:40.994)

Right, right. Yeah, okay. So, would you… If somebody was, I don’t know, maybe coming out of school now or maybe trying to change careers or something, are there some roles or functions that you would say, hey, you should spend your time up-leveling your skills in this area?

Peter Benei (13:42.924)

And I don’t want to be a training company.

Peter Benei (13:52.334)

Hmm?

Peter Benei (14:03.608)

So I’m 44. That will be a long shot, I’m 44 and many of my friends have kids who are like 15 or 10 or 15 or 20 sometimes. And they all talk about the same thing. I like full honesty.

John Jantsch (14:30.84)

Mm-hmm.

Peter Benei (14:33.39)

They talk about what will these kids will do in five to 10 years, what kind of careers they will pursue and so on and so on. They are families. So I usually talk with the dads, obviously, and they are talking about, I need to send my kid to a university or college or whatever. I live in Europe, so I don’t know, they send it to Vienna or something. And how…

How should I pick which university they should go in and so on and so on? How should I help them? And they are clueless. And usually the close to good answer that I see, and again, this is a personal opinion, so treat it as is, usually the ones that are sending their kids to some sort of like art, history,

John Jantsch (15:10.776)

Mm-hmm.

Right.

John Jantsch (15:31.512)

Mm-hmm.

Peter Benei (15:32.782)

Literally something around these like soft things, which we call soft skills or soft studies.

John Jantsch (15:37.376)

Mm-hmm.

John Jantsch (15:41.495)

Mm-hmm.

Peter Benei (15:44.692)

I wouldn’t send my kid to engineering school right now. I wouldn’t send my kid to learn that become a developer or a lawyer or not even a doctor probably. I don’t think that these, I mean, these professions will exist obviously, but it will have a really huge competition that only the finest one will succeed or will be needed.

but if you have like a general arts degree or something around that, know usually, you know, treated as totally useless. I have one by the way. but still, so I studied history and sociology pretty much useless, I guess, but still. and I think these, these studies might be something that can be valuable because they, they teach you the basics of.

John Jantsch (16:22.922)

Right?

Peter Benei (16:43.64)

how to read, how to judge aesthetic things, and how to think critically, yes. How to think in context, so like historical context, let’s say. And I think these baseline knowledge skills, let’s say, I wouldn’t call them skills, but these things will be in, yes.

John Jantsch (16:49.89)

I to think critically.

John Jantsch (17:08.704)

It’s exposure really more than anything else, right? Yeah.

Peter Benei (17:11.746)

These will be inherently valuable than knowing the latest legal, whatever it is.

John Jantsch (17:14.274)

Yeah, yeah.

John Jantsch (17:19.308)

Yeah, yeah, yeah, which can be, yeah, queued up. How about CMOs? Are you, do you see that role going away? Do you see it, you know, changing inside of organizations to where it will not only look different, but it will have a different function?

Peter Benei (17:22.541)

Yes.

Peter Benei (17:38.232)

So we preach at AERA, the CMO is that the CMO role is becoming more like an orchestrator who is leading and creating these environments of workflows where people work together with AI and AI automation. And from the marketing org chart, like, know, junior, mid-manager, specialist.

John Jantsch (17:47.81)

Mm-hmm.

Peter Benei (18:07.128)

head off whatever and see. I do think that the CMO role will be the last one who will fall. Juniors probably will have the hardest time, especially, and also mid managers and specialists, because some of them need to pivot into something else because AI will just simply eat their field of expertise there.

but those people who are able to manage not just people, but workflows together. mixing the soft skills with, I wouldn’t say engineering level skills of workflow engineering, but more like, you know, operational level. I think these people will be valuable and these people will be the CMOs I think. But if you were a CMO and only created the marketing budget and.

John Jantsch (18:53.516)

Mm-hmm.

Peter Benei (19:06.306)

delegated the tasks and that’s it. Yeah, you probably will have a harder time in the upcoming years and you need to learn workflow efficiency, operational level execute and you know, these kinds of Or if you are on the other side, more like an operational person, you probably need to learn a little bit more soft skills and judgment and taste and you know, these kinds of stuff that we talked about so far.

John Jantsch (19:35.124)

So I want end on one kind of, there’s a bit of been a bit of a rant for me and I’m curious where you land on this. I think a lot of people were jumping at, my AI tool stack is these 17 tools because they all do one thing really well. And I think what I’ve said all along is I think the Googles and the Microsofts of the world are going to basically figure out how to build all of those best of class tools into their

Peter Benei (19:41.774)

Please.

Peter Benei (19:51.342)

Hmm.

Peter Benei (20:03.448)

Agree.

John Jantsch (20:04.696)

into their work tool that you buy for one price or that you’re already buying that now is just $10 more a month. And they will really kind of wipe out a lot of these one-off tools. I’m curious what you think of that.

Peter Benei (20:10.926)

I agree.

Peter Benei (20:18.094)

100%. I mean, this will be a hard argument because I 100 % agree with you. I can share you two examples. Two examples and one explanation on why people think that. I mean, especially, know, C level people and decision makers, they love throwing resources on problems. So yeah, they have like a tool.

John Jantsch (20:43.352)

Mm-hmm.

Peter Benei (20:48.174)

abundance, and they, and they buy shiny new tools every day. that’s fine. We understand it’s obviously not the right call. and even, even they don’t, they know it usually. and the two examples are, are simple ones. One, you actually mentioned off of air that you read the latest article that we, that we published. I mean, it’s not rocket science judge, just a Claude Cowork, came out.

John Jantsch (21:16.941)

Yes.

Peter Benei (21:18.282)

A funny thing, by the way, did Claude did it. mean, the Anthropic team did it with Claude code within half, one and a half a week. And no line of code were written by any engineers, all AI. So the learning there is that most of the tools will be irrelevant because startups

John Jantsch (21:29.848)

Mm.

John Jantsch (21:34.934)

Yes.

Peter Benei (21:45.674)

And AI tools just die every day because new tools will come out. Also don’t forget that the big ones, Google and the others, they have infinite resources, like infinite. They have infinite training data and AI lives on data. So just like one simple AI feature added to Google ads, let’s say.

We’ll probably kill 90 % of the AI tools out there right now overnight.

John Jantsch (22:20.972)

Well, they also, know, one thing people underestimate, they also have all the hardware.

Peter Benei (22:25.216)

And also the hardware. Well, in a sense business, that hardware doesn’t really matter that much, more like the data, but yeah, the hardware is important too. And the second thing is that, well, I’m really proud of it because it happened today. So sorry for sharing it with everyone right now on this podcast, but I built a content repurposing application. You literally, it does…

John Jantsch (22:26.584)

So it doesn’t cost them anything.

John Jantsch (22:35.49)

Yeah. Yeah.

John Jantsch (22:45.208)

You

Peter Benei (22:54.956)

A simple thing, you give an RSS feed to the application, in our case, our newsletter. We are only two people. So we don’t have social media managers and stuff. And because most of the content that we do is news-driven, so every day we publish something new. We cannot batch write stuff pre-time. So we only know the content on the same day.

and we need to share it on X and everywhere. And we spend a lot of time to repurposing this type of content, even if we use AI. So this app actually takes everything that we have, new posts, and repurpose it on different platforms. It self-learns, it does everything. It’s fully automated, it’s amazing. It has a UX, everything.

and I built it under an hour while I having breakfast at my kitchen table. I’m not kidding. And I don’t know how to code at all. Like I never coded a single line of code ever. And I will probably never will. Claude did it. just why prompting it. So the reason why I’m telling this, thing is that it’s so easy to build up something new now.

John Jantsch (23:58.336)

Yeah.

Peter Benei (24:21.134)

even for personal use that you probably end up and that’s like a wild guess and more like a futurism. But I might guess that within a year or two, we don’t really even have like small sasses for most companies. People just, you know, ramp up their own applications for their own computer, for their own personal use, for their own agency, for their own clients within an hour.

John Jantsch (24:21.186)

Yeah. Right.

Peter Benei (24:50.508)

works fine just for them.

John Jantsch (24:53.016)

Yes. Yes, yes.

Peter Benei (24:54.382)

So it’s interesting. So short answer to your question. mean, don’t really bother subscribing to 20-something AI tools. Probably 95 % of them will be extinct within a year or two and substitute by Gemini or other Google products or whatever. Or second answer, build your own.

John Jantsch (25:05.237)

Alright.

John Jantsch (25:21.632)

Yeah, yeah. Yeah, I’m curious. And again, you don’t have to answer this. can end on this. But I suspect that Google will build a cowork clone, you know, because you think of all the people have all of their stuff on Google Drive, and not just to be able to say, here, go consume all this. You’ve got to believe that’s coming. Well, Peter, I appreciate you.

Peter Benei (25:31.853)

Yeah.

Peter Benei (25:41.25)

Yes. And by the way, it’s interesting. Sorry, last sentence. I have to rant about Microsoft a little. It’s so interesting that you have all the documents on SharePoints and all the knowledge documents and stuff, and copilot is still. So it’s so weird. Anyway, sorry.

John Jantsch (25:46.794)

No, yeah, yeah.

Mm-hmm.

John Jantsch (26:01.909)

huh. Yeah. Yeah, yeah.

No, no, no, it has that typical Microsoft feel will land there. So Peter, I appreciate you taking a few moments to stop by. Is there some place you’d invite people to find out more about AI ready CMO?

Peter Benei (26:12.909)

Yeah.

Peter Benei (26:17.719)

Always.

Peter Benei (26:22.84)

Well, you just said it, AIReadyCMO.com. It’s free to subscribe. We share daily updates, daily intelligence. Every day it lands the one thing that you need to know about AI in marketing in your email box. Simple.

John Jantsch (26:25.954)

Yep, awesome.

John Jantsch (26:36.748)

Yeah, it is a newsletter that I read every day. appreciate it, All right, great. Well, appreciate you stopping by and hopefully maybe one of these days we’ll run into you on the road.

Peter Benei (26:42.476)

Thank you.

Peter Benei (26:50.358)

and anytime. Thank you very much for inviting me.

John Jantsch (26:51.797)

us.

John Jantsch (00:01.442)

Hello and welcome to another episode of the Duct Tape Marketing Podcast. This is John Jantsch and my guest today is Peter Benei. He is a marketing leader and strategist with 20 plus years of experience as a CMO for tech scale-ups and startups. He co-founded AI Ready CMO, a platform and newsletter focused on helping marketing leaders adopt AI strategically, not just tool by tool, but through frameworks, case studies and community learning.

Peter Benei (00:01.57)

Thanks.

John Jantsch (00:30.39)

So guess what we’re going to talk about today? AI. Peter, welcome to the show.

Peter Benei (00:34.634)

Welcome and thanks for inviting me.

John Jantsch (00:38.028)

So given that you and I were just talking off air, you know, I’ve got 30 plus years, you’ve got 20 plus years, how in your mind has, does AI or the advent of AI different than say, websites and social media and search, you know, that kind of came along as tool? Would you say that it’s just another flavor or is it fundamentally different?

Peter Benei (00:43.341)

Yeah.

Peter Benei (01:04.052)

both, I guess. I had my own agency as well. Jesus, 20 years ago. and it was a social media agency. So at that time it was like, so Facebook business pages just got introduced and everyone was talking about the clue train manifesto markets are conversations and you know, this kind of stuff, social media, web two. I don’t know if you’re familiar with the market or Brian Solis.

John Jantsch (01:05.879)

Yeah.

John Jantsch (01:19.584)

Yeah.

John Jantsch (01:24.384)

Yeah. Yeah. Yeah. Yeah. Yeah.

Peter Benei (01:33.262)

Yeah, he was just about talking about the conversational prism and I don’t know. So everyone was talking about like, know, social media is a thing. And we had this agency, which was a social media agency. But again, that was a new thing. I don’t really think that the whole AI, whatever it is right now is…

John Jantsch (01:33.432)

Of course, yeah, Brian’s been on the show.

Peter Benei (02:02.4)

is new in a sense of tools and technology for marketers. These are just things that we need to learn and adapt to in general sense, like we did for, I don’t know, Facebook business pages at that time or, I don’t know, Squarespace websites. you can drag and drop websites again now. That’s interesting. Although I think the business model for agencies and marketing teams will be fundamentally changed

John Jantsch (02:22.53)

Yeah.

Peter Benei (02:32.184)

because of this new AI tool, AI capabilities, AI agent, whatever, AI. And I think that will be interesting to see. again, agencies also changed and marketing teams also changed 10, five, 20 years ago. So I think we just need to be familiar and open to adapt to this new change. So I don’t…

John Jantsch (03:00.31)

Well…

Peter Benei (03:01.078)

dramatize or strategize or panic around this. You just need to adapt.

John Jantsch (03:08.056)

Yeah, it’s funny. There was a period of time where you had social media marketing agencies and digital marketing agencies, right? It was just like, oh no, we’re this flavor. And now it’s just like, no, it’s all just marketing. Right. So what are the things you write about a lot? And, and I, you know, I’m a subscriber to your newsletter and I really, there are a lot of people out there writing about AI hype, you know, like look at what this thing could do. But I think you guys have take a very,

Peter Benei (03:12.206)

Hmm?

Peter Benei (03:19.693)

Yes.

Peter Benei (03:25.944)

Thank you.

John Jantsch (03:35.352)

Like you said, not necessarily a dramatic hype approach, a very almost stand back approach of saying, look, we have to remain strategic. Human beings have a role, but maybe it’s changed. And so I really appreciate that take. So let’s get in a little bit to the changing, like the AI plus strategy, you know, plus humans approach, because there’s certainly a lot of hand wringing right now around all these jobs that are going to be wiped out.

What are people going to do? So what do you, let’s just divide it. What do you think is going to go away that these tools actually do better than humans? And what do you think is going to actually stay and perhaps not for a long time be replaced by humans or by machines.

Peter Benei (04:05.486)

Thanks.

Peter Benei (04:21.922)

No, that’s a tempting and also interesting question. One thing that I want to reflect quickly, the focus on non-hype bullshit and sorry for calling that way, non-hype framing of this whole entire new trend was also personal choice of ours with the newsletter, but also a strategic choice as well.

Obviously everyone is hyping around this whole thing. we are personally, we are getting a little bit older, I guess. And we are just not interested in the, the, in the defocusing of our audiences. So we made the conscious decision to kind of like stand still and observe a little bit more with a strategic eye. So that’s one thing. Second.

John Jantsch (05:09.921)

Mm-hmm.

Peter Benei (05:18.232)

To your question, I would love to have an answer, but I’m not afraid to say that I don’t know. think during these times that are changing, it’s really hard to know what will happen. And we are just migrating, by the way, the news that are to another platform. And I had to reread the old stuff that we wrote. When I say old, like half a year ago.

John Jantsch (05:37.858)

Mm-hmm.

John Jantsch (05:47.832)

All right.

Peter Benei (05:48.174)

And that will be a context to your answer, by the way. And I just read what we’d wrote like half a year ago and everything was so beginning at that stage still. Everything changed so fast within a couple of months. New tools came out, new concepts introduced to the public. And I’m not talking about like agents, like more like, know.

John Jantsch (06:04.375)

Mm-hmm.

Peter Benei (06:14.818)

working together with AI, human in the loop, and these kind of stuff. It’s so hard to predict because within this small time frame, everything has changed. I think what we can do to answer this question, and sorry for it, it takes a little bit longer, is that to nail down the basics that we think that it will be changing. And I think there are a couple of things that will change. And one that I’m…

almost 100 % sure it will change is that production of marketing materials and like marketing production in a sense, like content production, shall we say, will be either fully automated or it will not come with a high barrier of entry. It doesn’t have a high barrier of entry right now either, but it will have like a minimum barrier of entry with AI.

John Jantsch (06:54.614)

Mm-hmm. Mm-hmm.

Peter Benei (07:14.254)

That means a lot for agencies, by the way, for marketing teams, because we create, mean, like 80 % of our work as marketers are creating content. Now, if the content creation is almost automated by AI, what do we do? Right? That’s the question. Now I don’t have the answer, but I’m sure that we won’t create that much and that amount of content within our workload and work time.

Second, AI is getting perfect or better, shall we say. It’s always, know, tomorrow’s AI is 10x better than today’s AI. But it’s still not perfect. And the reason why it’s not perfect is that it still needs the human, us, to course, supervise, review, edit, whatever. So I think the…

human in the loop or human in the addition working with the AI, it will matter for now, for a couple of years at least. And third, we need to think that if production is not our job anymore, but we still need it, then where do we need it? And I think that’s the answer for your question here, that we need to be able to form strategies.

And what is the strategy, by the way, understanding the client need with empathy and suggest process to achieve the goals. are goals and that’s it. Pretty much that’s the bare bones, simple strategy. How do we produce more? sorry. How do we produce better content? Because production wise, it will be automated, but it still has to be good. We need taste.

John Jantsch (08:56.45)

Right.

John Jantsch (09:09.698)

Right.

Peter Benei (09:11.106)

We need quality, we need judgment, we review supervision. And how do we work better with AI is that if we understand the workflows and the processes as a kind of like operator of the entire show. So I think strategy, like empathy, taste and operational efficiency or workflow knowledge should be…

and will be important for marketers. And I’m safe to say these.

John Jantsch (09:44.822)

Yeah, you, you. Well, and I think you raise a real, I think at least right now, one of the differentiators, the barrier to produce, to producing, quantity is gone. however, I think the barrier to producing quality is still a real differentiator.

Peter Benei (10:03.042)

Yeah. Yeah, I agree. agree. And it just, know, AI just like highlighted how not many of us have taste and how not many of us can produce great content and how most of the content that we’ve used so far anyway was, well, wouldn’t say garbage, but like, you know, mediocre. And I think it’s super important to…

to highlight that previously you needed resources to produce high quality content. So if you wanted to do a Super Bowl level advertising, you needed DDB or or or whoever big agency. If you wanted to do a global media campaign, you needed a media agency or an insane marketing budget to go with that.

John Jantsch (10:37.901)

Yes.

Peter Benei (11:02.638)

If you wanted to produce a content library of whatever you have, like 100 eBooks or shit, you need 10, 50, whatever, copywriters or marketers to do that. Similarly happening in other industries. So if you wanted to do the new John Wick movie, you needed a Hollywood studio and so on. can go on and on.

John Jantsch (11:18.338)

Thanks.

Peter Benei (11:33.184)

Now you don’t need these resources. You need a laptop and an idea and I don’t know, hundred dollars for API credits. And pretty much that’s it. That’s it. That’s all you need. And judgment and taste and strategic mindset. And, know, these kinds of stuff that are human in innate human values and abilities, which AI cannot produce.

John Jantsch (11:36.205)

Mm-hmm.

John Jantsch (12:02.658)

Well, so that begs the question then, if we are going to still have humans involved, do we need different humans? A lot of us. If we built an organization, say, to produce stuff, you know, the copywriters, the graphic designers, that their whole output was the stuff, do we now need to hire for taste and for judgment and for brand intuition?

Peter Benei (12:17.602)

Mm-hmm.

Peter Benei (12:27.83)

I yes. I’m not the person who will tell you otherwise. And I’m also not the person who is in the business who helps you to do that. But if I would be in the business, I would immediately start some sort of like a training company or anything around that that helps people who have like basic skills through studies. Like, I don’t know.

John Jantsch (12:28.92)

the

Peter Benei (12:57.806)

creative arts or whatever, and upgrading them to be able to use those skills in a refined manner for multiple purposes. In our case, marketing. So yeah, people and companies should hire Prudence.

John Jantsch (12:59.661)

Right.

John Jantsch (13:13.496)

And I think I’ve actually seen on your website, aren’t you producing some courses or some master classes or something around those? Yeah, yeah, okay.

Peter Benei (13:21.302)

Yeah, we do some workshops. We do some workshops, but we are not a training company. So, so we didn’t within AI ready CMO, if you like pave to go to get a paid member, you obviously have access to some sort of like a workshop training program and some studies, but we are not a training.

John Jantsch (13:26.551)

Yeah, yeah.

John Jantsch (13:40.994)

Right, right. Yeah, okay. So, would you… If somebody was, I don’t know, maybe coming out of school now or maybe trying to change careers or something, are there some roles or functions that you would say, hey, you should spend your time up-leveling your skills in this area?

Peter Benei (13:42.924)

And I don’t want to be a training company.

Peter Benei (13:52.334)

Hmm?

Peter Benei (14:03.608)

So I’m 44. That will be a long shot, I’m 44 and many of my friends have kids who are like 15 or 10 or 15 or 20 sometimes. And they all talk about the same thing. I like full honesty.

John Jantsch (14:30.84)

Mm-hmm.

Peter Benei (14:33.39)

They talk about what will these kids will do in five to 10 years, what kind of careers they will pursue and so on and so on. They are families. So I usually talk with the dads, obviously, and they are talking about, I need to send my kid to a university or college or whatever. I live in Europe, so I don’t know, they send it to Vienna or something. And how…

How should I pick which university they should go in and so on and so on? How should I help them? And they are clueless. And usually the close to good answer that I see, and again, this is a personal opinion, so treat it as is, usually the ones that are sending their kids to some sort of like art, history,

John Jantsch (15:10.776)

Mm-hmm.

Right.

John Jantsch (15:31.512)

Mm-hmm.

Peter Benei (15:32.782)

Literally something around these like soft things, which we call soft skills or soft studies.

John Jantsch (15:37.376)

Mm-hmm.

John Jantsch (15:41.495)

Mm-hmm.

Peter Benei (15:44.692)

I wouldn’t send my kid to engineering school right now. I wouldn’t send my kid to learn that become a developer or a lawyer or not even a doctor probably. I don’t think that these, I mean, these professions will exist obviously, but it will have a really huge competition that only the finest one will succeed or will be needed.

but if you have like a general arts degree or something around that, know usually, you know, treated as totally useless. I have one by the way. but still, so I studied history and sociology pretty much useless, I guess, but still. and I think these, these studies might be something that can be valuable because they, they teach you the basics of.

John Jantsch (16:22.922)

Right?

Peter Benei (16:43.64)

how to read, how to judge aesthetic things, and how to think critically, yes. How to think in context, so like historical context, let’s say. And I think these baseline knowledge skills, let’s say, I wouldn’t call them skills, but these things will be in, yes.

John Jantsch (16:49.89)

I to think critically.

John Jantsch (17:08.704)

It’s exposure really more than anything else, right? Yeah.

Peter Benei (17:11.746)

These will be inherently valuable than knowing the latest legal, whatever it is.

John Jantsch (17:14.274)

Yeah, yeah.

John Jantsch (17:19.308)

Yeah, yeah, yeah, which can be, yeah, queued up. How about CMOs? Are you, do you see that role going away? Do you see it, you know, changing inside of organizations to where it will not only look different, but it will have a different function?

Peter Benei (17:22.541)

Yes.

Peter Benei (17:38.232)

So we preach at AERA, the CMO is that the CMO role is becoming more like an orchestrator who is leading and creating these environments of workflows where people work together with AI and AI automation. And from the marketing org chart, like, know, junior, mid-manager, specialist.

John Jantsch (17:47.81)

Mm-hmm.

Peter Benei (18:07.128)

head off whatever and see. I do think that the CMO role will be the last one who will fall. Juniors probably will have the hardest time, especially, and also mid managers and specialists, because some of them need to pivot into something else because AI will just simply eat their field of expertise there.

but those people who are able to manage not just people, but workflows together. mixing the soft skills with, I wouldn’t say engineering level skills of workflow engineering, but more like, you know, operational level. I think these people will be valuable and these people will be the CMOs I think. But if you were a CMO and only created the marketing budget and.

John Jantsch (18:53.516)

Mm-hmm.

Peter Benei (19:06.306)

delegated the tasks and that’s it. Yeah, you probably will have a harder time in the upcoming years and you need to learn workflow efficiency, operational level execute and you know, these kinds of Or if you are on the other side, more like an operational person, you probably need to learn a little bit more soft skills and judgment and taste and you know, these kinds of stuff that we talked about so far.

John Jantsch (19:35.124)

So I want end on one kind of, there’s a bit of been a bit of a rant for me and I’m curious where you land on this. I think a lot of people were jumping at, my AI tool stack is these 17 tools because they all do one thing really well. And I think what I’ve said all along is I think the Googles and the Microsofts of the world are going to basically figure out how to build all of those best of class tools into their

Peter Benei (19:41.774)

Please.

Peter Benei (19:51.342)

Hmm.

Peter Benei (20:03.448)

Agree.

John Jantsch (20:04.696)

into their work tool that you buy for one price or that you’re already buying that now is just $10 more a month. And they will really kind of wipe out a lot of these one-off tools. I’m curious what you think of that.

Peter Benei (20:10.926)

I agree.

Peter Benei (20:18.094)

100%. I mean, this will be a hard argument because I 100 % agree with you. I can share you two examples. Two examples and one explanation on why people think that. I mean, especially, know, C level people and decision makers, they love throwing resources on problems. So yeah, they have like a tool.

John Jantsch (20:43.352)

Mm-hmm.

Peter Benei (20:48.174)

abundance, and they, and they buy shiny new tools every day. that’s fine. We understand it’s obviously not the right call. and even, even they don’t, they know it usually. and the two examples are, are simple ones. One, you actually mentioned off of air that you read the latest article that we, that we published. I mean, it’s not rocket science judge, just a Claude Cowork, came out.

John Jantsch (21:16.941)

Yes.

Peter Benei (21:18.282)

A funny thing, by the way, did Claude did it. mean, the Anthropic team did it with Claude code within half, one and a half a week. And no line of code were written by any engineers, all AI. So the learning there is that most of the tools will be irrelevant because startups

John Jantsch (21:29.848)

Mm.

John Jantsch (21:34.934)

Yes.

Peter Benei (21:45.674)

And AI tools just die every day because new tools will come out. Also don’t forget that the big ones, Google and the others, they have infinite resources, like infinite. They have infinite training data and AI lives on data. So just like one simple AI feature added to Google ads, let’s say.

We’ll probably kill 90 % of the AI tools out there right now overnight.

John Jantsch (22:20.972)

Well, they also, know, one thing people underestimate, they also have all the hardware.

Peter Benei (22:25.216)

And also the hardware. Well, in a sense business, that hardware doesn’t really matter that much, more like the data, but yeah, the hardware is important too. And the second thing is that, well, I’m really proud of it because it happened today. So sorry for sharing it with everyone right now on this podcast, but I built a content repurposing application. You literally, it does…

John Jantsch (22:26.584)

So it doesn’t cost them anything.

John Jantsch (22:35.49)

Yeah. Yeah.

John Jantsch (22:45.208)

You

Peter Benei (22:54.956)

A simple thing, you give an RSS feed to the application, in our case, our newsletter. We are only two people. So we don’t have social media managers and stuff. And because most of the content that we do is news-driven, so every day we publish something new. We cannot batch write stuff pre-time. So we only know the content on the same day.

and we need to share it on X and everywhere. And we spend a lot of time to repurposing this type of content, even if we use AI. So this app actually takes everything that we have, new posts, and repurpose it on different platforms. It self-learns, it does everything. It’s fully automated, it’s amazing. It has a UX, everything.

and I built it under an hour while I having breakfast at my kitchen table. I’m not kidding. And I don’t know how to code at all. Like I never coded a single line of code ever. And I will probably never will. Claude did it. just why prompting it. So the reason why I’m telling this, thing is that it’s so easy to build up something new now.

John Jantsch (23:58.336)

Yeah.

Peter Benei (24:21.134)

even for personal use that you probably end up and that’s like a wild guess and more like a futurism. But I might guess that within a year or two, we don’t really even have like small sasses for most companies. People just, you know, ramp up their own applications for their own computer, for their own personal use, for their own agency, for their own clients within an hour.

John Jantsch (24:21.186)

Yeah. Right.

Peter Benei (24:50.508)

works fine just for them.

John Jantsch (24:53.016)

Yes. Yes, yes.

Peter Benei (24:54.382)

So it’s interesting. So short answer to your question. mean, don’t really bother subscribing to 20-something AI tools. Probably 95 % of them will be extinct within a year or two and substitute by Gemini or other Google products or whatever. Or second answer, build your own.

John Jantsch (25:05.237)

Alright.

John Jantsch (25:21.632)

Yeah, yeah. Yeah, I’m curious. And again, you don’t have to answer this. can end on this. But I suspect that Google will build a cowork clone, you know, because you think of all the people have all of their stuff on Google Drive, and not just to be able to say, here, go consume all this. You’ve got to believe that’s coming. Well, Peter, I appreciate you.

Peter Benei (25:31.853)

Yeah.

Peter Benei (25:41.25)

Yes. And by the way, it’s interesting. Sorry, last sentence. I have to rant about Microsoft a little. It’s so interesting that you have all the documents on SharePoints and all the knowledge documents and stuff, and copilot is still. So it’s so weird. Anyway, sorry.

John Jantsch (25:46.794)

No, yeah, yeah.

Mm-hmm.

John Jantsch (26:01.909)

huh. Yeah. Yeah, yeah.

No, no, no, it has that typical Microsoft feel will land there. So Peter, I appreciate you taking a few moments to stop by. Is there some place you’d invite people to find out more about AI ready CMO?

Peter Benei (26:12.909)

Yeah.

Peter Benei (26:17.719)

Always.

Peter Benei (26:22.84)

Well, you just said it, AIReadyCMO.com. It’s free to subscribe. We share daily updates, daily intelligence. Every day it lands the one thing that you need to know about AI in marketing in your email box. Simple.

John Jantsch (26:25.954)

Yep, awesome.

John Jantsch (26:36.748)

Yeah, it is a newsletter that I read every day. appreciate it, All right, great. Well, appreciate you stopping by and hopefully maybe one of these days we’ll run into you on the road.

Peter Benei (26:42.476)

Thank you.

Peter Benei (26:50.358)

and anytime. Thank you very much for inviting me.

John Jantsch (26:51.797)

us.