Last year, I made a bet that changed how I think about the future of financial regulation in the age of ai.. Here's what happened.
As AI becomes more powerful and autonomous, how will financial regulators keep up? I’m exploring the future of financial regulation in the age of AI, from the challenges of regulating black-box algorithms to the potential for AI-powered supervision. This is a critical conversation for the future of finance.
What I've Learned From 85 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with the future of financial regulation in the age of ai..
The biggest misconception is that you need to you need to move fast and break things. That's backwards. The companies that win are the ones that the best solutions are often the simplest ones.
I remember sitting with the Anthropic team early on and discussing how they thought about the future of financial regulation in the age of ai.. Their approach was counterintuitive but brilliant.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to the future of financial regulation in the age of ai. are fundamentally flawed. Not slightly off. Fundamentally flawed.
The root cause is usually one of three things:
- Copying what big companies do without understanding why they do it. What works for Google doesn't work for a 10-person startup.
- Over-engineering the solution when a simple approach would work better. I've seen teams spend six months building something that could have been done in two weeks.
- Ignoring the human element. Technology is the easy part. Getting people to actually use it is where the real challenge lives.
The Reality Nobody Talks About
Most people approach the future of financial regulation in the age of ai. with assumptions that made sense five years ago. The world has moved on. When I look at my portfolio companies, the ones that succeed are doing something fundamentally different.
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.
At RemoteTeam, we learned this the hard way. We spent months going down the wrong path before realizing that you need to move fast and break things. Once we made the switch, everything changed.
What I Tell Founders
When a founder in my portfolio asks me about the future of financial regulation in the age of ai., I usually start with three questions:
- What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
- What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
- Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.
These questions seem simple but they reveal a lot about where a company actually stands.
This connects to broader themes around algorithmic trading, AI fraud detection, AI risk management, AI banking that I've been thinking about a lot lately.
The Bottom Line
Look, the future of financial regulation in the age of ai. isn't 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 the future of financial regulation in the age of ai. aren't the ones with the best strategy on paper. They're the ones who execute, learn, and adapt faster than everyone else.
I've been doing this for over a decade. The patterns are clear. The companies that take the future of financial regulation in the age of ai. seriously outperform the ones that don't. Every single time.
If you're working on something interesting in this space, I'd love to hear about it. Drop me a line.
Frequently Asked Questions
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.
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.
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.