I got a call a few months ago from a founder I’d invested in. He was panicked. He’d just lost his best machine learning engineer to a FAANG company for a compensation package that sounded more like a rounding error in their cloud computing budget than a salary. Seven figures. For a guy three years out of his PhD program.
My reaction? I told him to let him go. In fact, I told him it was a good thing.
For the past few years, everyone in Silicon Valley has been obsessed with the “AI talent wars.” The narrative has been all about scarcity. A desperate scramble for a handful of geniuses who can build the next generation of large language models. We’ve seen headlines about nine-figure compensation packages and entire teams being acqui-hired just to get their hands on a few key people. It’s been a frenzy, and it’s been mostly a lie.
The AI talent wars are over. And the winner isn’t who you think.
It’s not Google, or Meta, or even OpenAI. It’s not the researchers with the fancy papers and the massive Twitter followings. The real winners are the quiet ones. The builders. The people who are actually using AI to solve real-world problems.
The Great AI Headfake
I’ve been lucky enough to have a front-row seat to this whole circus. As a founder who has been through two exits and now as an angel investor in over 200 companies, including some of the big names in AI like Anthropic, OpenAI, and Scale AI, I’ve seen the hype cycle from the inside. And let me tell you, the obsession with “top AI talent” has been one of the biggest headfakes in recent tech history.
For a while, the thinking was that if you could just hire the smartest people from the top labs, you’d win. The belief was that AI was a game of pure intellectual horsepower. The company with the most PhDs from Stanford and MIT would build the best models and conquer the world. So we saw a gold rush. Companies were throwing money at anyone who had ever published a paper at NeurIPS. It was a classic bubble, driven by ego and fear.
But here’s the thing about bubbles: they always pop. And the AI talent bubble is no exception.
What happened? A few things. First, the big models started to get commoditized. What was once a monumental feat of engineering that only a few companies in the world could achieve is now becoming more and more accessible. Open-source models are getting surprisingly good. And the cost of training and running these models is dropping, albeit slowly.
Second, and more importantly, people started to realize that having the biggest, most powerful model wasn't the same as having a business. A model is not a product. A model is a tool. And what matters is not how fancy your tool is, but what you can build with it.
The Rise of the AI Artisans
This is where the real winners of the AI talent war are emerging. They’re not the model builders. They’re the model users. The people who have a deep understanding of a specific industry and can see how to apply AI to solve a real, painful problem. I call them the AI artisans.
These are the people who are building companies in industries that the Silicon Valley elite would consider “boring.” Logistics. Manufacturing. Agriculture. Healthcare. These are not the sexy, headline-grabbing applications of AI. But they are the ones that are creating real value. And they are the ones that are building sustainable, profitable businesses.
I have a portfolio company that is a great example of this. They’re in the construction industry. Not exactly the first place you’d think to look for cutting-edge AI. But they’ve built a system that uses computer vision to analyze drone footage of construction sites and identify potential safety hazards. It’s not the most glamorous application of AI. But it’s saving lives. And it’s a great business.
They couldn’t afford to hire the “star” AI researchers. They couldn’t compete with the seven-figure salaries. So they hired people who knew construction. People who had spent their careers on job sites and understood the real-world problems that needed to be solved. And then they taught them the AI. Or rather, they gave them the tools to apply the AI.
This is the future of AI. It’s not about a small number of geniuses building ever-larger models. It’s about a large number of people with domain expertise using AI to solve problems in their own fields.
What This Means for You
So what does this mean for you? Whether you’re a founder or an engineer, the end of the AI talent war has big implications.
For founders:
- Stop chasing the rockstars. You don’t need to hire the most famous AI researcher in the world. You need to hire people who understand your customers and your market. People who are passionate about solving the problem you’re trying to solve.
- Focus on data, not models. Your competitive advantage is not going to be your model. It’s going to be your data. The unique, proprietary data that you can use to train your models and create a product that no one else can replicate.
- Think small. You don’t need to build a massive, general-purpose AI. You need to build a small, specialized AI that is really, really good at solving one specific problem.
For talent:
- Don’t be a model builder. Be a problem solver. The most valuable skill in the new AI economy is not the ability to build a model. It’s the ability to identify a problem and figure out how to use AI to solve it.
- Go deep on a domain. Become an expert in a specific industry. Learn the language, the workflows, the pain points. That’s where the real opportunities are.
- Join a mission-driven company. The big tech companies can offer you a lot of money. But they can’t offer you the chance to be part of something that really matters. The most talented people I know are not motivated by money. They’re motivated by mission.
The War is Over, The Real Work Begins
The AI talent war was a distraction. It was a sideshow. It was a product of a moment in time when the technology was new and no one really knew what to do with it. But that moment is over.
Now the real work begins. The work of building real products, solving real problems, and creating real value. And the people who are going to do that work are not the ones with the fanciest degrees or the biggest salaries. They’re the ones with the deepest understanding of the world and the biggest passion for making it better.
So if you’re a founder, stop worrying about the talent war. And if you’re an engineer, stop chasing the money. The war is over. And the winners are the ones who are building the future, one real-world problem at a time.
Frequently Asked Questions
How has this view evolved over time?
My thinking on most topics has changed significantly over the years. Early in my career, I held many conventional views that experience proved wrong. I try to update my beliefs when the evidence changes.
What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 200+ startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.