I've managed over $8M in remote team payroll and seen every hybrid work AI 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 in you
The Framework That Actually Works
Here is a simple framework for evaluating hybrid work AI. 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: most founders overthink this and underspend on execution
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 that get hybrid work AI right treat it as an ongoing process, not a one-time project.
What I've Learned From 101 Companies
A few patterns in hybrid work AI come up again and again.
The founders who handle hybrid work AI well understand that most founders overthink this and underspend on execution.
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 AI performance reviews, AI coworking, async communication AI that I've been thinking about a lot lately.
Final Thoughts
There are no shortcuts in hybrid work AI, but there are smarter paths.
The strongest teams treat hybrid work AI as a competitive advantage, not a checkbox. They invest in it early, measure it obsessively, and never stop improving.
If you're just getting started with hybrid work AI, don't be intimidated. Everyone starts somewhere. The key is to start with the right mindset and the right framework, and then execute like your company depends on it. Because it probably does.
Frequently Asked Questions
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: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'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.