I can’t match FAANG salaries, but I move fast and give people real responsibility and a meaningful mission. This is how I bring in top AI talent with opportunities big tech can’t offer.
What I've Learned From 108 Companies
A few patterns in AI talent come up again and again.
The founders who handle AI talent well understand that the best solutions are often the simplest ones.
The Framework That Actually Works
Here is a simple framework for evaluating AI talent. It's not complicated, but it requires discipline.
Step 1: the market doesn't care about your roadmap
This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: your team matters more than your technology
Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly
Nothing works perfectly the first time. The companies that get AI talent right treat it as an ongoing process, not a one-time project.
The Numbers Don't Lie
Investing early in AI talent can be the difference between raising your next round and running out of runway.
One of my portfolio companies went from struggling to profitable in under a year after they finally got serious about this. The founder told me later that they wished they'd started sooner.
This connects to broader themes around AI pitch decks, AI exit strategies, AI due diligence, AI market sizing, AI startup pivots that I've been thinking about a lot lately.
Final Thoughts
There are no shortcuts in AI talent, but there are smarter paths.
The strongest teams treat AI talent as a competitive advantage, not a checkbox. They invest in it early, measure it obsessively, and never stop improving.
If you're just getting started with AI talent, don't be intimidated. Everyone starts somewhere. The key is to start with the right mindset and the right framework, and then execute like your company depends on it. Because it probably does.
Frequently Asked Questions
Q: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 234 startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
Q:How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
Q:Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
Q: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.