A founder asked me last week about the truth about our first failed ai feature. My answer surprised them, and it might surprise you too.
I didn't go to business school. I learned how to build a multi-million dollar AI company from the trenches. After countless mistakes and a few lucky breaks, I've distilled my experience into these 7 hard-won lessons. This is the stuff they don't teach you in books.
The Reality Nobody Talks About
Most people approach the truth about our first failed ai feature 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 simplicity beats complexity every time. Once we made the switch, everything changed.
What I've Learned From 64 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 truth about our first failed ai feature.
The biggest misconception is that you need to the market doesn't care about your roadmap. 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 the truth about our first failed ai feature. Their approach was counterintuitive but brilliant.
Why Most Approaches Fail
Let me be direct: about 70% of the approaches I see to the truth about our first failed ai feature 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.
What I Tell Founders
When a founder in my portfolio asks me about the truth about our first failed ai feature, 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 feature prioritization ai, failure, startups that I've been thinking about a lot lately.
What's Next
The world of the truth about our first failed ai feature 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 the truth about our first failed ai feature 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
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.
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.