Companies take opposite approaches to AI threat detection, and the one you'd expect to win often doesn't.
After analyzing 100+ AI Threat Detection incidents, I found a terrifying pattern. This is what you need to know before it's too late.
The Counterintuitive Truth
In AI threat detection, the best practitioners often do less, not more.
The lesson: the market doesn't care about your roadmap. It sounds simple. It's incredibly hard to execute.
What I've Learned From 126 Companies
Across 234 angel investments, including Anthropic, a few patterns in AI threat detection come up again and again.
The founders who handle AI threat detection well understand that the data tells a different story than your gut.
The Numbers Don't Lie
The gap between companies that take AI threat detection seriously and those that don't is usually clear.
Investing early in AI threat detection 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 zero-day AI, AI security tools, adversarial AI, AI threat detection 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 threat detection 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 threat detection 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: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.