I Achieved the Four-Hour Workweek. So, Why Did I Just Take a Job?

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In 2023, 12 years after reading The 4-Hour Work Week, I was making enough passive income from my Udemy course on prompt engineering to achieve the Tim Ferriss dream.

I didn’t need a job. Yet I decided to trade freedom for a monthly paycheck again when I joined Every in February full-time to lead tech consulting and write.

My friends are puzzled. Isn’t the course making more money than ever (despite what the prompt engineering haters say)? What will it be like having a boss after five years of self-employment and six years building a company before that? Don’t you remember vowing to never take another job?

My answer is that it’s the best time in history to join a company. AI has made it easier to build new products, but it hasn’t made it easier to find customers. Entrepreneurship has arguably gotten harder. Deploying AI within a company that’s already working beats building the fifth version of a product that nobody will use. Plus, you can learn things inside a company that never get shared on X.

Making money the hard way

On paper, I had it made. I had no boss, could work from anywhere, and made money while I slept. The reality is that solo is harder than it looks.

I make money from my online course because I spent many sleepless (and unpaid!) nights working with GPT-3 for years before ChatGPT was released and AI went mainstream. I gave up lucrative data science retainers to take on AI projects, slashed my day rates 75 percent, and even worked for free, because I was excited by the potential and wanted to learn.

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I could have never predicted that any of this would pay off, and I also can’t predict when it will end. Sometimes I worked on the course every day, other times I went months without updating it, and nothing seems to make a difference to revenue. I’ve created two other AI courses— both flopped. Passive income may sound great, but it is a fickle beast.

It wasn’t just the course. Almost all the work I did as an entrepreneur started with months of unpaid work. I worked for two months without a paycheck when I started my marketing agency, and only started paying myself six figures when we scaled past 30 people. I worked for three months for free on a data science project as a learning exercise before turning that into a seven-figure consulting practice. I spent a year writing a prompt engineering book for O’Reilly before I saw my first royalty check.

Then there were the failures. The video editor and content repurposing tool that never got a single customer. The marketing book I wrote that only 200 people read. The product I spent months on and never got released after a cofounder falling-out. The list goes on.

Friends who run startups report similar low batting averages, and most successful entrepreneurs have many more failures than they do wins. The hardest thing to cope with, however, is the uncertainty.

It’s grueling to not know whether the thing you’re pouring all your effort into is going to work. If it fails, where is your next paycheck coming from? You’re too busy to set up the next thing, but the current thing isn’t working well enough to bet your career on. Every time I work on a new product, I question whether this will be the one that sinks me. I constantly worry that I have run out of good ideas.

You spend so much time working on the business that you don’t get time to do the work that attracted you to it in the first place. Your days are filled with customer calls to find what to build next, and then you have to code late at night to build it. You’re doing finance and legal admin on the weekend instead of learning new skills. All the fun experiments you want to run have to be set aside for the boring stuff that makes enough revenue in the short term to keep you afloat.

Don’t start a startup unless there’s nothing else you can imagine doing. Most of the time, the quality of life and economics are worse than getting a normal job. I achieved the four-hour work week. It just came with 40 more hours of worry.

Exposure to the frontier of AI

I proved I could build things on my own, but given the pace of AI, so many people are now flooding the market with vibe coded ideas. The chances of my next project getting attention above that noise are rapidly shrinking.

This was my primary motivation for taking the job at Every. The company already had product market fit across several products, and a media business with distribution to more than 100,000 subscribers. If I build something in Every, I can share it with our subscribers so it can be used, and that gives me more license to experiment than I could have toiling away on my own. I don’t have to justify experimenting with the latest model or worry about my token budget.

It’s paradoxical, but I’m finding the learning to be faster-paced inside a company than it was on my own. In another situation, I’d be “the AI guy” being asked what OpenClaw is, spending hours figuring it out so I had a useful take. At Every, on my first day, I found a Discord channel called “#only-claws” where my colleagues’ OpenClaw agents could talk to each other.

Seeing the team use Claws convinced me to reconsider my initial skepticism, and now I have three Claws running 24/7. It’s not all on me to run a discovery process on every new idea—I can ask someone who’s already played around. The social relationships you form in a company act as an idea filter, helping you determine what’s real versus what’s over-hyped.

There is another important part of my full-time role: I am living in New York, where Every’s headquarters are based. Part of the reason I relocated from the U.K. this year was that I believe the only”‘alpha”—inside information that can confer an economic advantage—left is in person. People share things in person that they don’t put online. The moment something is online, then AI can train on it, and if AI can do it, then everyone else in the market can do it too. Being in the room where things happen lets me feed my curiosity and build my knowledge, and maximizes my chances of being early on whatever does end up being the next big thing.

I heard Dan give a non-obvious insight on “claw-human” psychology on a call, and when I asked him about it later, he directed me to a tweet he had written I hadn’t seen. I have already cited his insight in two different client meetings. As a follower on X, I might have seen his take eventually, but as an employee, I got to ask my own questions about it. Outside the company, I would have eventually figured this insight out, but inside, I get to help shape it. It’s like the difference between passively watching a movie and actively playing a video game.

I don’t think I’m the only one making this calculation—giving up freedom and self-employment to work with a team on AI.

Investor and author Byrne Hobart joked that job offers at Anthropic come with a negative $10 million salary—you have to pay to work there—in return for getting to read their upcoming blog posts and tweets 24 hours in advance. That information is worth gold, given how much the market moves when the company publishes something new. He’s kidding, but the underlying logic is real: Proximity to the frontier is so valuable that it changes what the math on a “good deal” looks like.

Sharing the cool stuff

The narrative at the moment is that AI is leading to new business formation and acts as a great equalizer for small businesses. There’s even talk of the first billion-dollar one-person company. I believe those milestones will be achieved, yet I don’t want to be the person who builds it.

Some of the happiest moments in my previous businesses were when I had grown enough to build a team around me to take some of the burden off my shoulders—and watch someone on the team do something cool without my help. That pride you feel when the company is winning, and you can take a vacation without everything falling apart.

After five years on my own, I never had a big enough hit to build out a team. I was doing cool stuff, but only a handful of people knew about it. I had freedom, but with limited impact.

For the past decade, the smart move was to build alone and own everything yourself. AI has brought down the barriers to building, so the most important thing now is knowing what to build. Knowing that requires being in the right rooms and having the right conversations.

So I’ve traded the four-hour workweek for a forty(ish)-hour one. I’ve never learned faster.

Mike Taylor is the head of tech consulting at Every and a co-author of the O’Reilly-published Prompt Engineering for Generative AI. You can follow him on X at @hammer_mt and on LinkedIn.

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