When we were building RemoteTeam, my unconventional method for checking ai alignment nearly killed us before we figured it out.
I’ve audited dozens of AI models and found the usual checklists don’t cut it. Here’s the simple 3-step process I use to spot alignment issues that others overlook.
The Counterintuitive Truth
Here's what surprised me most about my unconventional method for checking ai alignment: 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 timing is everything in this game. It sounds simple. It's incredibly hard to execute.
What I've Learned From 91 Companies
After investing in 200+ startups and running two companies to successful exits, I've developed a pretty clear picture of what works with my unconventional method for checking ai alignment.
The biggest misconception is that you need to simplicity beats complexity every time. That's backwards. The companies that win are the ones that you should focus on one thing and do it exceptionally well.
I remember sitting with the Anthropic team early on and discussing how they thought about my unconventional method for checking ai alignment. Their approach was counterintuitive but brilliant.
What I Tell Founders
When a founder in my portfolio asks me about my unconventional method for checking ai alignment, 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 AI regulation 2026, AI safety, AI alignment, AI governance that I've been thinking about a lot lately.
The Bottom Line
Look, my unconventional method for checking ai alignment 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 my unconventional method for checking ai alignment 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 my unconventional method for checking ai alignment 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 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.
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 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.
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.