Many founders give up on AI coworking just before it starts to work.
I almost gave up on AI coworking until I discovered a simple shift in perspective that changed everything. In this post, I'm breaking down the exact framework that took our team from struggling to soaring, increasing our efficiency by 75%.
What I've Learned From 70 Companies
A few patterns in AI coworking come up again and again.
The founders who handle AI coworking well understand that timing is everything in this game.
The Counterintuitive Truth
In AI coworking, the best practitioners often do less, not more.
The lesson: timing is everything in this game. It sounds simple. It's incredibly hard to execute.
Real Talk: What Actually Matters
Here is what actually matters in AI coworking.
First, execution speed beats perfection. Every time. Companies rarely fail because they moved too fast on AI coworking. 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 AI coworking in a vacuum. Get out of the building. Talk to real people.
This connects to broader themes around AI onboarding, hybrid work AI, AI culture building, 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 AI coworking right on day one. You just need to get started and keep improving.
Founders who do well at AI coworking 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 can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
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.
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: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.