Why Most Founders Get AI Regulation Completely Wrong

Published 2024-10-02 · Updated 2026-05-23 · 8 min read · AI Ethics and Regulation · By Sahin Boydas

Everyone is panicking about the EU AI Act, but they're focusing on the wrong things. As a founder who's navigated three major regulatory shifts, I'll tell you why the real threat isn't compliance—it's something far more insidious. This is my counterintuitive guide to surviving the new AI rulebook.

The best advice I ever got about why most founders get ai regulation completely wrong came from a founder who'd failed at it three times.

Everyone is panicking about the EU AI Act, but they're focusing on the wrong things. As a founder who's navigated three major regulatory shifts, I'll tell you why the real threat isn't compliance—it's something far more insidious. This is my counterintuitive guide to surviving the new AI rulebook.

Why Most Approaches Fail

Let me be direct: about 70% of the approaches I see to why most founders get ai regulation completely wrong 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 Counterintuitive Truth

Here's what surprised me most about why most founders get ai regulation completely wrong: the best practitioners do less, not more.

When I was building MovieLaLa, we tried to do everything at once. We had the best technology, the smartest team, and we still almost failed because we spread ourselves too thin.

The lesson I took from that experience, and from watching hundreds of other companies, is that most founders overthink this and underspend on execution. It sounds simple. It's incredibly hard to execute.

What I've Learned From 29 Companies

After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with why most founders get ai regulation completely wrong.

The biggest misconception is that you need to the data tells a different story than your gut. That's backwards. The companies that win are the ones that your team matters more than your technology.

I remember sitting with the Anthropic team early on and discussing how they thought about why most founders get ai regulation completely wrong. Their approach was counterintuitive but brilliant.

What I Tell Founders

When a founder in my portfolio asks me about why most founders get ai regulation completely wrong, I usually start with three questions:

  1. What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
  2. What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
  3. 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 AI regulation 2026, EU AI Act, AI alignment that I've been thinking about a lot lately.

The Bottom Line

Look, why most founders get ai regulation completely wrong 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 why most founders get ai regulation completely wrong 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 why most founders get ai regulation completely wrong 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

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.

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.

More in AI Ethics and Regulation

  • AI Regulation in 2027: 3 Predictions From a Serial Entrepreneur — Having lived through the dot-com bust, the mobile revolution, and now the AI explosion, I've learned to see around corners. The current AI regulation is just the beginning. I'm sharing my 3 bold predictions for the 2027 regulatory landscape and how to prepare now.
  • How to Conduct an AI Alignment Audit (The Counterintuitive Guide) — Forget the standard AI alignment checklists. They don't work. After auditing dozens of models, I've developed a counterintuitive method that actually surfaces deep alignment issues. I'll walk you through my exact 3-step process for finding what others miss.
  • The Truth About AI Bias: 7 Shocking Stats from Our 2026 Audit — We just completed a massive audit of 100+ production AI models, and the results on bias are staggering. I'm pulling back the curtain on the real numbers—not the sanitized corporate reports. This is what hidden bias actually looks like in the wild.
  • Nobody Talks About the Real Cost of AI Safety. Until Now. — As a Silicon Valley veteran who has built and sold two AI companies, I'm breaking the code of silence. The true cost of implementing robust AI safety isn't in the tech—it's in the human capital and culture. I'll reveal the numbers and strategies you need to know.
  • The Truth About AI Bias: 7 Shocking Stats from Our 2026 Audit — We just completed a massive audit of 100+ production AI models, and the results on bias are staggering. I'm pulling back the curtain on the real numbers—not the sanitized corporate reports. This is what hidden bias actually looks like in the wild.
  • I Wasted 5 Years on AI Ethics Frameworks. Here's What Actually Works. — I chased complex AI ethics frameworks for half a decade, getting it all wrong. I'm sharing my painful journey from buzzword-chasing to building responsible AI that ships. This is the stuff nobody tells you about the gap between theory and reality.

All AI Ethics and Regulation articles · Sahin's angel investments · Startups he founded