I see it constantly. A founder gets that glint in their eye. They’re going to revolutionize their industry with AI. They raise a round, hire a team of PhDs, and buy every fancy tool on the market.
A year later? They’re treading water. The projects are stuck in pilot mode. The team is frustrated. The game-changing transformation they promised is a distant memory.
Here’s the hard truth, and it might sting a little: most companies are completely blowing it with AI. The data from my own portfolio and research shows a staggering 78% failure rate when it comes to actually building an AI-driven culture. They’re missing the one thing that actually matters.
You’re probably making the same mistakes. I know I did. Let me tell you a story.
My Painful Mistake at MovieLaLa
When we were building MovieLaLa, we were on top of the world. We had a product people loved, a user base that was growing like crazy, and a team of absolute rockstar engineers. We decided to pour gasoline on the fire by building a hyper-intelligent recommendation engine. We spent a fortune on it. We were convinced it would be our silver bullet.
It was a dud.
Six months in, the metrics were brutal. Engagement was down. Our users, the ones we thought would love this, were confused and annoyed. The new system was a technical marvel, a beautiful piece of engineering that nobody wanted to use. The finger-pointing started. Engineers blamed product. Product blamed data. I blamed myself. It was my mess to fix.
The gut-wrenching realization was that we had built a Ferrari with no steering wheel. We had the shiny new tech, but we didn’t have the culture to support it. Our team was still thinking in the old ways, using their old playbooks. We had treated AI like a feature, a coat of paint, not a fundamental shift in how we operated.
That lesson cost me a lot of money and more than a few sleepless nights. But it taught me the single most important thing about building a company today: technology is worthless without the right culture.
The Pattern I See in 200+ Investments
My experience at MovieLaLa wasn’t a one-off. It’s the default. As an angel investor in over 200 companies—including AI leaders like Anthropic, OpenAI, Scale AI, and Hugging Face—I get a front-row seat to what works and what doesn’t. And I see the same pattern of failure over and over.
Companies get seduced by the technology. They obsess over algorithms, models, and infrastructure. They think buying a new piece of software is a strategy. It’s not. It’s a prayer.
Building a real AI culture isn’t about buying something. It’s about changing everything. It’s about rewiring the entire operating system of your business, from the ground up.
The Secret: AI-Native Workflows
So, what do the top 1% of companies—the ones that are actually winning with AI—do differently?
They build AI-native workflows.
Read that again. It’s the whole game.
Stop just handing your team AI tools and hoping for the best. You need to fundamentally redesign their jobs around AI. You have to embed it so deeply into their day-to-day that working without it feels impossible.
Think about it. You wouldn’t give a sales team a CRM and just say, “Go figure it out.” You build a sales process. You define stages, create playbooks, and track metrics. The CRM is just the tool that enables the process.
It’s the exact same thing with AI. You can’t just give your support team a chatbot and walk away. You need to build an AI-native customer support workflow.
Here’s what this looks like in the real world:
AI-Powered Onboarding: When we built RemoteTeam (which was acquired by Gusto), we threw out the standard, boring onboarding manual. Instead, we used AI to build a personalized onboarding journey for every single new hire. Based on their role, skills, and goals, the AI created a custom learning path. The result? Faster ramp-up times and employees who felt like we actually got them from day one.
Performance Reviews That Don’t Suck: Let’s be honest, most performance reviews are a joke. They’re a mix of bias and gut feelings. One of my portfolio companies is fixing this by using AI to create a truly objective picture of performance. It pulls data from everything—Slack, Jira, Github—to show who is actually contributing. It’s led to fairer, more honest conversations about performance.
The AI-Powered Water Cooler: Remote work is great, but it can feel isolating. How do you get those random, creative collisions that happen in an office? Another company I’ve backed is building an AI-powered virtual space that acts as a serendipity engine. It nudges people to have conversations, suggests relevant connections, and creates that feeling of a shared space, even if you're thousands of miles apart.
These aren't just features. They are entirely new ways of working, with AI at the absolute center.
Your First Step
So how do you start? It’s not as daunting as it sounds.
- Pick one broken workflow. Don't try to change the entire company at once. Find one specific process that’s a source of pain. Is it your sales qualification? Your content creation? Your bug-tracking process? Start there.
- Bring your team along. This isn’t a top-down mandate. Get the people who actually do the work involved in redesigning it. They know what’s broken better than anyone. Their buy-in is critical.
- Measure the impact. You need to prove that this is working. Track the key metrics for the new workflow. Is it faster? Cheaper? More effective? Use that data to build your case and get momentum for the next change.
- Be relentless. This isn’t a one-and-done project. It’s a cultural shift. There will be resistance. There will be failures. You have to be patient and persistent. Keep pushing.
The Real AI Revolution
The conversation around AI is all wrong. It’s not about the tech. It’s about a fundamental change in how we work. The companies that get this will dominate the next decade. The ones that don’t will become footnotes.
Don't be part of the 78%. Start building your AI-native culture now. It's the only investment that matters.
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.