I've been in the Silicon Valley trenches for over a decade, and I've never seen a shift as massive as AI in healthcare. I'm sharing the hard-won lessons from my own startups and investments-the wins, the failures, and the counterintuitive strategies that actually work.
What I've Learned From 54 Companies
A few patterns in AI drug discovery come up again and again.
The founders who handle AI drug discovery well understand that the data tells a different story than your gut.
The Counterintuitive Truth
In AI drug discovery, the best practitioners often do less, not more.
The lesson: your team matters more than your technology. It sounds simple. It's incredibly hard to execute.
The Reality Nobody Talks About
A lot of the advice on AI drug discovery rests on assumptions that made sense five years ago. The world has moved on.
The first thing to understand is that timing is everything in this game. I've seen this play out across dozens of companies. The pattern is unmistakable.
Many teams spend months on the wrong path before realizing that you should focus on one thing and do it exceptionally well. Once they make the switch, everything changes.
Real Talk: What Actually Matters
Here is what actually matters in AI drug discovery.
First, execution speed beats perfection. Every time. Companies rarely fail because they moved too fast on AI drug discovery. Many fail because they moved too slowly.
Second, measure everything. If you can't measure it, you can't improve it. Set up tracking from day one, even if it's basic.
Third, talk to your users. It sounds obvious, but many founders make decisions about AI drug discovery in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around biotech AI, AI mental health, healthcare automation that I've been thinking about a lot lately.
The Bottom Line
None of this is rocket science. But it does require intentionality, consistency, and a willingness to learn from mistakes.
If you take one thing from this article, let it be this: start now, start small, and iterate. The founders who win at AI drug discovery aren't the ones with the best strategy on paper. They're the ones who execute, learn, and adapt faster than everyone else.
Companies that take AI drug discovery seriously tend to pull ahead of the ones that don't.
If you're working on something interesting in this space, I'd love to hear about it. Drop me a line.
Frequently Asked Questions
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: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.