Stop Teaching Your Team AI. Keep the Top 40%.

7 Sep 2026 · 19 min · 7 chapters

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In short

Don’t “teach” your team AI; instead hire top talent (keep roughly the top 40%) and use AI as a tool to draft/optimize work while testing and tracking what’s actually productive.

Guests

Neil (co-host/founder retreat organizer; argues mindset can’t be trained—people either have it or don’t) and the other speaker (VC-backed entrepreneur; discusses CEO priorities: talent, finance, vision; shares AI misuse and marketing lessons).

Key claims

mindset isn’t teachable; CEO’s job is hiring exceptional people; AI can draft in brand voice using customer data; AI often becomes a sycophant/hallucinates and wastes time if you keep prompting for agreement.

Notable examples

Slack/GitHub leaderboard used to identify low-activity engineers; ChatGPT “therapist” loops with no progress; GEO example where an accounting partner repeatedly prompted ChatGPT to rank his firm #1, but other colleagues/CFO got different results.

Written by AI. May contain mistakes. Listen to the episode to check what was said.

Chapters

Tap a time to open that second in VO

The Talent Bar: Keeping the Top 40%

0:12 to 0:26

Discover the importance of hiring top talent and managing team efficiency.

“Drafting campaign copy, blog posts, emails, all in your brand voice.”

The Talent Bar: Keeping the Top 40%

0:31 to 2:55

Discover the importance of hiring top talent and managing team efficiency.

“So Neil, we're planning out this founder retreat that we do every year.”

Mindset in Hiring and Training

2:55 to 4:53

Explore the challenges of teaching mindset versus hiring skilled individuals.

“And I think everyone's waking up to trying to teach someone mindset, train them on mindset is not something you can do.”

Navigating Problems and Solutions

6:29 to 13:20

Understand how to approach problems effectively without overthinking.

“And if it seems like a fit, We'll get in touch and help you with a free marketing plan.”

AI Hallucination and Productivity

13:20 to 14:00

Learn about the pitfalls of relying on AI for personal and professional growth.

“and it would actually end up driving you crazy, right?”

Understanding AI Limitations in Recommendations

14:00 to 17:06

Explore a real-world example highlighting AI's shortcomings in company recommendations.

“It was less than that, but it was more than five.”

Lessons on AI Understanding for Executives

17:07 to 17:38

Discuss the ongoing challenges executives face in grasping AI technology.

“So with Neil's example here, I think there's a little lesson to learn as well.”
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Transcript

Automatic transcript. May contain errors.

0:00Eric Siu:You know that feeling when the strategy is done, the brief is written, everyone's aligned, and you realize someone still has to sit down and actually create all the content? That someone is you, and it's due tomorrow. Breeze Assistant can help. It works right inside HubSpot. Drafting campaign copy, blog posts, emails, all in your brand voice. All grounded in your actual customer data. So you don't just create content. You create content that converts. check out HubSpot.com, the agentic customer platform for growing businesses. So Neil, we're planning out this founder retreat that we do every year.

0:37Eric Siu:And I was talking to this group. And in the beginning of the year, we're like, you know, we're going to go hard on these AI hackathons, these transformation, all these things. Everyone at the end of this, this is September now. We did this retreat in February. We're like, F all that. None of that works. okay we're just like just unrisomely high just talent bar now and you get everything that you need and the the thing is uh one of the guys we're talking to let's say he has like uh 200 engineers for example right now if you think about it how many of the 200 do you think are uh you know acceptable from a like a talent bar standpoint what percent depends on the company

1:17Neil Patel:if it was anthropic it would be a very high percentage yeah i don't know like you know What kind of company?

1:22Eric Siu:Most of us are, you know, in software, right? Software, services, whatever. So it's like... How old is the company? No, you're able to pinpoint.

1:30Neil Patel:I'm not going to say anything. You can give me a random industry if it's in... Let's say this company's been around for 15 years. 15 years? That means they probably don't fire a lot of people. A lot of people with them for a long time. Maybe they're happy with 5%, 10%. Okay.

1:45Eric Siu:It's actually much higher. About 40%. Okay. Okay. So, but, so someone else on the call was like, well, like, okay, so what are you gonna do with the rest? Well, and then, so what happens is, like, I'll give you an example. For us, in our Slack, we have a GitHub leaderboard, okay? It shows how much someone is committing, how much someone is merging, how much someone is reviewing. So these are all GitHub terms. It just shows how much you're pushing to GitHub, right? And so he has it for the engineers, and it's a public leaderboard, okay? And you can see who's shipping a lot, who isn't. And imagine, if I'm engineer that works for you and I have like 2 ,000 lines of code in a week and I have no like no commits and no merges, right?

2:28Eric Siu:That means I'm not really that active. And so he has a lot of people that are like that. I can see kind of something that are similar with mine. So, and so like, what are you going to do? He's like, you know, there's no, you might have to keep the top 40%, which are the good ones, but you might have to keep like another 20%, but the rest you're going to have to let go, right? And so anyway, that's, it's just interesting how we started the year, like, oh, we're super like, you know, we're going to teach everyone this stuff. And Neil's always been a proponent of, no, you're just not going to teach them.

2:55Eric Siu:And I think everyone's waking up to trying to teach someone mindset, train them on mindset is not something you can do.

3:01Neil Patel:My big take is whether there's this new technology or not, I've always for many, many years just said hire really amazing people and it solves most problems. I did not come up with this venture capitalists from all the major firms tell their entrepreneurs the same thing that's actually how i learned it wasn't through reading article from a16z or anything like that when i raised money for kissmetrics back in the day tony uh phil black who was one of the co-founders of true ventures they did um i think i know they did wordpress i don't know if he was a personal investor in Uber. And they did quite a few other deals.

3:42Neil Patel:I don't know if they were in Slack or not, but I know they did like Blue Bottle Coffee. They had some amazing hits. Would always tell me your number one job is just hire a really, really good people who can do every little thing you have a problem in exceptionally well. And they know the solution. They don't have to learn it. They've already done it. They've already solved it. And they can teach you things and you aren't the one teaching them new shit. And he's like, if you can hire those kinds of people for every role, he's like, your company will succeed. Those people will figure out. That's your only job.

4:16Eric Siu:So there's three jobs of a CEO and Neil doesn't officially have a title, but the three jobs of a CEO is one, talent. Okay, so talent, recruiting, however you want to look at it. Two is finance, keeping money in the bank or even closing big deals. Okay, and the third one is your vision, right? It's really those three things. And so when I heard that when I was 25, because I like reading all these books, I'm like, no, that's BS, right? But the older you get, you realize how true these things are. And the older we get to, so Neil and I would go to these events, right? And you hear these people say, you know, everything about entrepreneurship is just mindset.

4:45Eric Siu:And it is. But like what I've said before on this podcast is that you cannot train mindset and it's not on you to have to babysit and train someone on mindset. The people come and build with mindset. And like I've told you, by the way, we just, we hired a 15 year old, right? I think I told you about that. That mindset's already there, right? He had that mindset starting in second grade, for example. Now I'm looking, I'm talking to, I don't care what age you are. There's guy I'm talking to in his 60s right now, mindset's there, right? Super on top of his stuff, super into the AI stuff as well. And so you didn't start with this mindset.

5:13Eric Siu:I didn't start with it, but we built ourselves into it. I'm not saying you and I are amazing. I'm just saying that, again, thinking that you can teach someone mindset is a fool's errand.

5:23Neil Patel:But I know you like doing your retreats and I get why, you know, these people are your friends and you guys have fun. But imagine how much time you would save if you didn't do the stuff like, hey, we're going to do all these AI boot camps and all this stuff. We're just going to hire it. And then you guys want to go have fun during that time. We do have fun during it, though. No, but you would have just had more fun and less time wastage. Well, here's the thing.

5:47Eric Siu:You have a problem. If you're building an e-commerce brand, you should check out DTC Pod, hosted by Ramon Berrios and Blaine Bolas on the HubSpot Podcast Network. They speak with founders, marketers, creators, agencies, and platform experts about what it actually takes to grow a direct-to-consumer business from paid ads and influencer marketing to conversion, email, brand building, and consumer trends. I particularly enjoyed their conversations around scaling a brand without losing what made customers care in the first place. Listen to DTC Pod wherever you get your podcasts. Problems, right? Real quick, if you want to acquire customers faster and more efficiently this year with the latest strategies and tactics, then check out singlegrain.com.

6:25Eric Siu:That is my ad agency. Again, www.singlegrain.com. Check it out. And if it seems like a fit, We'll get in touch and help you with a free marketing plan. In life, you have problems. Don't overthink this one. Yeah, but not really.

6:40Neil Patel:I think people look at life as like you have problems and people like discussing with others to go figure out solutions. Most people's problems aren't really problems and there's already solutions that exist to solve them. That's how I look at life. Like seriously, that's how I really look at life.

6:57Eric Siu:Okay, so the reason I ask that question is because we all have problems. I mean, I always like to complain about our problems and you like to complain about your problems to people that understand, right? No, I don't like complaining to friends about problems. Well, you're different. You're like, you're different. Most normal human beings, Neil's not a normal human being, right? Complain about their problems. Like Noah, you talk about your problems with somebody else, right? Yeah. Noah's nodding, right? People like that, but I don't.

7:18Neil Patel:I've always been more just get to the point and solve it.

7:20Eric Siu:Cause you're not like a introspective therapy guy. You're like move forward, which is a good thing, right? Like a lot of people in VC now, like Mark Andreessen is like, you know, move forward. you know uh what is it uh retard maxi right just look for it no no intersection just look for and i think you've always been like that to your credit but i think most humans you're not a very emotional human for the most part unless someone screws you over from i've known anyone for like 16 years now but majority humans they like to talk about their problems so yeah but it's it's fun like by the way the reason i talk about this retreat too like i'm planning it this year right we're going to this uh the four seasons tamarindo which is a new one by the way 2023 and uh it's not super packed yet.

7:57Eric Siu:It's like still 30, 40 % capacity. See, now it might blow it up. I don't know. Right. Probably not. But what are we going to do there? We're going to play tennis. We're going to play pickleball. We're going to talk about our problems, but it's like, oh, I can make this interest. Like you never know, by the way, certain business deals that come out of that. It's always from like a conversation that's in passing, right? Yes.

8:14Neil Patel:One quick thing. You said the R word with maxing. You should probably explain what that is because most people want and they're going to take it the wrong way.

8:21Eric Siu:Okay, so retard maxing is the act of not thinking about your past, right? It's not looking, thinking about introspection. It's not thinking about, oh, my past or ruminating on the past, right? It's just constantly thinking about moving forward every single day. And even if you make a mistake, that's okay, move forward. And that is how Neil has operated. I'm not saying, by the way, I'm not calling Neil an R word. I'm not calling you an R word. And in fact, I think the Overton window has passed. It's okay to say that more today. But anyway, my point is, is it helpful to introspect? In hindsight, not necessarily, right?

8:55Eric Siu:I think most of the time it's just helpful to get hit a few times and just move forward.

9:00Neil Patel:Like right now in today's world, I know so many more people that use chat GPT as a therapist than I would have ever imagined. and people start going to these LLMs and start having conversations like they would with a human. So I understand why humans discuss their problems or issues and try to work on solutions. But what I'm noticing when I talk to the people that are using these LLMs for this, they're not actually doing it to be productive to figure out a solution. They're doing it to complain and be like, this is my viewpoint. This is what happened. What do you think? they're not actually using it to be more um efficient's the wrong word but like they're

9:46Eric Siu:not using it to move forward they're not advancing work yes they're not advancing work or even their

9:51Neil Patel:personal life they're using it to someone like kind of like a real human to complain to and i'm

9:56Eric Siu:like what the heck is this so you know that uh remember i was i was going through something maybe like two years ago right it was like um and then i kept i realized when i was in this pattern i was going into i was using it as a therapist right well this happened over here in this relationship this happened, this and that. And then it just kept putting me in a loop and it kept agreeing with me. And then at the end of it, I'm like, wait, I made no progress. It's perceived progress.

10:18Neil Patel:Correct. And I remember when you're going through that, we were all telling you, if you have to, at least me and another mutual friend of yours, if you have to put all this stuff into AI, it's just not meant to be. But on the flip side, with your mom's passing, it's been more than a

10:39Neil Patel:the process, how it is like, feeling, is this all normal? And that aspect, I thought it was very helpful for you from an outsider's perspective. You know what was the most helpful?

10:49Eric Siu:You saw the poem that that was the most beautiful thing. That's the best example of using it, right? Because my mom, I had her fill out this book called Mom, Tell Me Your Story, right? At the end of it, she wrote in Chinese and she knows I can't, like my Chinese, like you use her to lose it, right? So I had lost it already. So she wrote like three pages and I'm like, I can't read this, right? So I took screenshots of it and I put it in chat, and I wrote the most beautiful poem ever. But what that reinforces to you is that, you know, human working with it. So my mom's work plus the AI was something that became beautiful.

11:23Eric Siu:And I actually took it out and I framed it two times. But it was, it was her wisdom. And it's like, you know, I'm ending my chapter here, but like, you know, I hope you get married to someone of AZ. And, you know, you want her to believe in you, that type of stuff, right? And so that's how you use AI to actually advance work.

11:40Neil Patel:Yes. But I think a lot of people have to go through learnings and waste time. And then, you know, they go from there. Eric learns on his own. He learns pretty quickly. Even if I tell him something, whether it's true or not, whether my way is right or wrong, Eric will do it. And he'll learn within like a week or a month on, you know, what is more optimal in the future. And then he makes a mental note of it. and then going forward, he makes sure he doesn't make the same mistake over and over again. And I think that's the key, whether it's in entrepreneurship or marketing. You know, like when we run campaigns, you can now have AI make the mental notes for you, but you want to keep track of what's working, what's not, so you can fine tune and get better.

12:22Neil Patel:But the key here is when Eric used AI or ChatGPT two years ago for a personal situation, it starts hallucinating and siding with you. Even in today's world, AI still does hallucinate and it starts feeding you what it thinks you want. Maybe not as much as it did two years ago, but I still see it doing that in many cases when I look at conversations. It's not hallucinating, it's a sycophant,

12:48Eric Siu:which means it agrees with you on everything.

12:50Neil Patel:Yeah, there you go. That's actually a better way to put it. But yeah, it agrees with you and then you start drinking your own Kool-Aid.

12:56Eric Siu:Yeah, and it's like, oh, it reinforces more and more that you're right when you're actually wrong because you find a way to justify everything. And by the way, when I think about that interaction, in the moment, I'm like, yeah, absolutely, I'm right. But when I look at it, I'm like, that was such a waste of time. And that was like 20 plus hours spent on it. Like that time, like it didn't, the context window would fill very quickly. And so I had to start a new chat and I had to make a carryover chat. And I just kept repeating over and over and it would actually end up driving you crazy, right? So anyway, all that to say is like, Neil and I, we're not saying we're right on everything.

13:28Eric Siu:We're just saying you have to test these things. And ideally, if you don't feel like you're actually being productive, you're probably not being productive. Which, by the way, you called out ChatGPT OpenAI. I wanted to call out what I believe is OpenAI's boneheaded GPT-6 astral launch.

13:42Neil Patel:But before you go to that, you want to hear the most entertaining, going back to the hallucination and agreeing with you part. Example I have for GEO. What? I was talking to a global accounting firm. so they specialize in helping you optimize taxes you know for all the countries that you generate revenue from and one of the guys i was talking with is a partner at this firm it's a large firm and he's just like yeah i got really pissed off uh chat gpt doesn't recommend our firm he wasn't the founder it's big it's where the partners eventually just own and then you rinse and repeat and your partners come in he's like they don't recommend our company and i was like what were you typing he's like oh i asked chat gpt all these questions related to it so i was like this is a zoom call so i'm like do you mind screen sharing opening up so he opens up a chat gpt instance and he starts with the question and i'm paraphrasing here but what are the 10 best or not what are the 10 best?

14:46Neil Patel:What are the best accounting firms that you would recommend if I'm a company that operates in multiple countries and I'm looking for a global accounting company that can help us optimize for taxes and they're headquartered in the US. And it lists out five or 10. It wasn't actually 10. It was less than that, but it was more than five. It lists out on a table some of these companies that they should not reach. Their company is more well-known, bigger than the competitors. So then he asked chat GPT a follow-up question. Why didn't you recommend my company, company X? We do X, Y, and Z. And then he's like, you're right.

Read the full transcript

15:23Neil Patel:I was just looking at the surface level. I didn't dig deeper, but when I dug deeper, it actually, you know, your company is more qualified and it breaks on all this kind of stuff. And then he asked other similar questions to, hey what's the best firm to help me bring money over from the uk to the united states that can help me bring over money not just with existing money but going forward in the most tax efficient way and he keeps asking more follow-up questions and every single follow-up question is listing his company as the number one slot and the one to choose and he's just like look it's now starting to understand i'm like no it's not starting to understand it's just agreeing with you and then i show him on my end i'm asking the same questions his company is not even listed yeah i'm like you're just it's starting to agree with you and he had no joke probably like 16 17 different prompts that he was following up with and it keeps agreeing with him in the future i'm like it's just learning based on what keeps you happy giving you that and feeding you too but when other potential customers ask it's not showing up and this zoom call was me my cfo and one other people in the accounting so then i had my cfo go ask the same question on his end you know same exact one that the other guy was asking and then we had the another person ask and then he had one other colleague based in chicago i believe uh so different office than his also asked none of us got his firm and i'm like even your colleague who works at your company isn't getting i'm like it's just agreeing with you this is what happens you got to actually optimize for it not just keep asking follow-up questions and assuming that other people will get the same response that you're looking for.

17:06Eric Siu:But also how long has AI been out for? Three years? Three, four years. Okay, so three, four years. So with Neil's example here, I think there's a little lesson to learn as well. It's been out for three years and even executives or partners at large companies still don't understand how this stuff works, right? And so it often takes time for people to catch up and understand it and the world still doesn't get it yet, right? That it's a sycophant and it's going to listen to whatever. And so take that for what it is. So that's the lesson. Keep being consistent. That's how you wind up marketing.

17:36Neil Patel:Yep. All right. Goodbye.

From the publisher

Growth Newsletter: https://levelingup.beehiiv.com/subscribeNeed marketing help? Visit: https://www.singlegrain.com/ and https://npdigital.com/Want to recruit great marketers? Find them here: https://marketingschool.io/hireEric came back from a founder retreat with a hard truth: the AI hackathons and training programs everyone planned in January didn't work, and the companies pulling ahead just raised the talent bar. He walks through the GitHub leaderboard that shows who's actually shipping, why one 200-engineer company is keeping only its top 40, and Neil's long-held view that you can't train mindset. Then the sycophancy trap: why ChatGPT agrees with whatever you feed it, what Neil found when he ran a real recommendation test across an accounting firm, and why most executives still don't understand how these models work.

Key takeaways◾You can't train mindset. Raise the bar and hire people who already have it◾A public shipping leaderboard exposes who's really working in about a week◾AI is a sycophant. Optimize for it, don't just ask it follow-up questions

Chapters00:00 Stop training, raise the talent bar01:14 The GitHub leaderboard: keep the top 4002:31 Neil: hire amazing people, it solves most problems07:45 The AI therapy trap: it agrees with you13:17 Neil's accounting-firm recommendation test15:54 Three years in, executives still don't get it

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