AI Makes You A Learning Machine Or A Lazy Machine
Episode
20 min
Read time
2 min
Topics
Productivity, Remote Work, Relationships
AI-Generated Summary
Key Takeaways
- ✓AI User Dichotomy: AI amplifies existing work habits rather than replacing them. Users who ask more questions and probe deeper become faster learners, while those who offload all thinking produce low-quality output. The differentiator is whether someone uses AI to expand their thinking or to avoid thinking entirely — a choice with compounding consequences over time.
- ✓ChatGPT Ad Performance: ChatGPT ads deliver 256% higher lead quality than Meta and a 46% lower cost per acquisition, but trail Google by 49% on lead quality. However, Google's CPA runs significantly higher. For marketers prioritizing cost efficiency, ChatGPT ads represent an early-mover window before pricing rises, accessible now via a new Criteo partnership.
- ✓AI Ranking Revenue Cliff: Data from Neil's agency shows ChatGPT and similar LLMs are far more winner-take-all than traditional search. Position one captures nearly all revenue, position two earns roughly 32% of that, position three drops to 8%, and position four falls to approximately 1% — making LLM brand visibility a critical priority for businesses.
- ✓AI Agents Inside Team Channels: Deploying AI agents directly into Slack workspaces — across sales, recruiting, and SEO channels — creates a self-reinforcing feedback loop. Agents pull data, generate strategies, rate existing plans, and offer to execute tasks. Teams rate the utility at 10 out of 10, and the next evolution is configuring agents to function as personalized performance coaches per employee.
- ✓Train AI, Not Employees: A scalable consulting opportunity exists in training company-specific AI systems to adapt to human workflows rather than retraining employees to use AI. This model mirrors Bain or McKinsey but focuses exclusively on optimizing AI outputs for each organization's context — covering marketing, engineering, and operations — and is more practical than broad employee AI training programs.
What It Covers
Eric Siu and Neil Patel examine how AI divides users into active learners versus passive dependents, share data on ChatGPT ad performance versus Meta and Google, reveal AI ranking revenue drop-offs, and discuss deploying AI agents inside Slack to coach and performance-manage teams in real time.
Key Questions Answered
- •AI User Dichotomy: AI amplifies existing work habits rather than replacing them. Users who ask more questions and probe deeper become faster learners, while those who offload all thinking produce low-quality output. The differentiator is whether someone uses AI to expand their thinking or to avoid thinking entirely — a choice with compounding consequences over time.
- •ChatGPT Ad Performance: ChatGPT ads deliver 256% higher lead quality than Meta and a 46% lower cost per acquisition, but trail Google by 49% on lead quality. However, Google's CPA runs significantly higher. For marketers prioritizing cost efficiency, ChatGPT ads represent an early-mover window before pricing rises, accessible now via a new Criteo partnership.
- •AI Ranking Revenue Cliff: Data from Neil's agency shows ChatGPT and similar LLMs are far more winner-take-all than traditional search. Position one captures nearly all revenue, position two earns roughly 32% of that, position three drops to 8%, and position four falls to approximately 1% — making LLM brand visibility a critical priority for businesses.
- •AI Agents Inside Team Channels: Deploying AI agents directly into Slack workspaces — across sales, recruiting, and SEO channels — creates a self-reinforcing feedback loop. Agents pull data, generate strategies, rate existing plans, and offer to execute tasks. Teams rate the utility at 10 out of 10, and the next evolution is configuring agents to function as personalized performance coaches per employee.
- •Train AI, Not Employees: A scalable consulting opportunity exists in training company-specific AI systems to adapt to human workflows rather than retraining employees to use AI. This model mirrors Bain or McKinsey but focuses exclusively on optimizing AI outputs for each organization's context — covering marketing, engineering, and operations — and is more practical than broad employee AI training programs.
Notable Moment
Neil's agency data reveals that enterprise deals — over the past three months — close almost entirely through personal relationships rather than inbound or outbound channels, suggesting that as AI commoditizes execution, human trust networks become the primary driver of high-value B2B revenue.
Episode Transcript
Using only 20% of your business data is like dating someone who only texts emojis. First of all, that's annoying. And second, you're missing a lot of context, but that's how most businesses operate today, using only 20% of their data. Unless you have HubSpot where all the emails, call logs and chat messages turn into insights to grow your business because all that data makes all the difference. I would know because I use HubSpot at my company. Learn more at hubspot.com. I've realized recently that AI either makes you more of a learning machine or more of a lazy machine. So the people that use AI, for example, I'm gonna, I'm gonna guess for Neil. Neil probably asks a lot of tax questions to his AI. Okay. So more or less as a tax strategist. Right? You're learning more. There's I'm sure there's a lot that you've learned about things that you just didn't know before. Right? But my point is you've you're asking a lot more questions that you usually would have asked before. You're not just kind of, you know, expect like, taking it and say, oh, AI do the work for me. So when I say AI makes you a learning machine, you ask more questions and you actually expand your mind more. That's for smart people. Okay? Now, unfortunately, many people, many people, like, you wanna be, you wanna be lazy and smart. You don't wanna just be lazy. Okay? So because smart and lazy people try to figure out ways around things. Right? They figure out creative ways. But if you're just someone that just throws it over defense and you're just like, ChatTeeBee is gonna solve the problems, ChatTeeBee will write my prompts for me, ChatTeeBee is gonna write all the content for me, Then you will get slopped. Right? So that's the first point I wanna make. But the second point to the to to what you're saying is I've had my AI agents, they've started to invade my Slack channels. Right? Mhmm. And so they're working in my my my sales room. They're working in my recruiting room. They're working in the SEO room too, and it's working with the team. Now here's the thing. I see it their team's asking for data polls, and it it's giving the team strategies, outside the box strategies, and it's rating our strategies, and it's also offering to do the work too. Now Now here's the other thing that you just mentioned that gave me an idea. So we Neil and I just made an idea, baby. Let us let the everyone know that we just made a baby. So the idea, baby, that we made here, Neil, is if you have it coaching your team, okay, like imagine your your your kids are gonna be working with personalized AI tutors. Right? Everyone on your team now has a personalized, coach. Okay. That has all the data that understands what that team's supposed …
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Tools
by OpenAI
“Eric Siu and Neil Patel examine how AI divides users into active learners versus passive dependents, share data on ChatGPT ad performance versus Meta and Google, reveal AI ranking revenue drop-offs, and discuss deploying AI agents inside Slack to coach and performance-manage teams in real time.”
by Criteo
“For marketers prioritizing cost efficiency, ChatGPT ads represent an early-mover window before pricing rises, accessible now via a new Criteo partnership.”
by Slack Technologies
“Deploying AI agents directly into Slack workspaces — across sales, recruiting, and SEO channels — creates a self-reinforcing feedback loop.”
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