Everyone thinks they know hybrid work AI, but they're missing the most important piece of the puzzle. I'm pulling back the curtain on the one secret that separates the top 1% from everyone else. This might be controversial, but the data doe
The Reality Nobody Talks About
A lot of the advice on hybrid work AI rests on assumptions that made sense five years ago. The world has moved on.
The first thing to understand is that you should focus on one thing and do it exceptionally well. I've seen this play out across dozens of companies. The pattern is unmistakable.
Many teams spend months on the wrong path before realizing that customer feedback is the only metric that matters. Once they make the switch, everything changes.
What I've Learned From 23 Companies
A few patterns in hybrid work AI come up again and again.
The founders who handle hybrid work AI well understand that you should focus on one thing and do it exceptionally well.
Why Most Approaches Fail
Many common approaches to hybrid work AI are flawed at the root.
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.
Real Talk: What Actually Matters
Here is what actually matters in hybrid work AI.
First, execution speed beats perfection. Every time. Companies rarely fail because they moved too fast on hybrid work AI. Many fail because they moved too slowly.
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. It sounds obvious, but many founders make decisions about hybrid work AI in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around async communication AI, AI onboarding, digital nomad AI tools, AI performance reviews that I've been thinking about a lot lately.
Wrapping Up
I've shared a lot here, and I know it can feel overwhelming. But you don't need to get hybrid work AI right on day one. You just need to get started and keep improving.
Founders who do well at hybrid work AI tend to share one trait: they're relentlessly practical. They don't chase perfection. They chase progress.
That's the mindset I'd encourage you to adopt. Start where you are. Use what you have. Do what you can. And keep pushing forward.
As always, I'm rooting for you.
Frequently Asked Questions
Q: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.
Q: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.
Q: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 234 startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.