Two of my portfolio companies had opposite approaches to why most founders get ai culture building completely wrong. The one you'd expect to win didn't.
I've managed over $10M in remote team payroll and seen every AI culture building mistake in the book. This is the culmination of a decade of experience, distilled into actionable advice you can implement today to see immediate improvements
The Framework That Actually Works
I'm going to share the exact framework I use when evaluating why most founders get ai culture building completely wrong. It's not complicated, but it requires discipline.
Step 1: customer feedback is the only metric that matters This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: the data tells a different story than your gut Once you have the foundation right, this becomes much easier. I've watched founders struggle with this for months when the answer was staring them in the face.
Step 3: Iterate relentlessly Nothing works perfectly the first time. The companies in my portfolio that nail why most founders get ai culture building completely wrong are the ones that treat it as an ongoing process, not a one-time project.
The Reality Nobody Talks About
Most people approach why most founders get ai culture building completely wrong 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 the data tells a different story than your gut. 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 your team matters more than your technology. Once we made the switch, everything changed.
Real Talk: What Actually Matters
I'm going to cut through the noise and tell you what actually matters when it comes to why most founders get ai culture building completely wrong.
First, execution speed beats perfection. Every time. I've never seen a company fail because they moved too fast on why most founders get ai culture building completely wrong. I've seen plenty fail because they moved too slow.
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. This sounds obvious but you'd be amazed how many founders build their why most founders get ai culture building completely wrong strategy in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around hybrid work AI, AI culture building, AI performance reviews that I've been thinking about a lot lately.
What's Next
The world of why most founders get ai culture building completely wrong is moving fast. What worked last year might not work next year. That's both the challenge and the opportunity.
My advice: stay curious, stay humble, and stay close to the people who are actually doing the work. Read less thought leadership and do more experiments. Talk to fewer consultants and more practitioners.
And if you're a founder building in this space, remember that the best time to get why most founders get ai culture building completely wrong right is before you need to. Don't wait for a crisis to force your hand.
I'll keep sharing what I learn. This stuff matters too much to keep to myself.
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 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.
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.