Last year, I made a bet that changed how I think about 7 counterintuitive lessons i learned managing a remote. Here's what happened.
Managing an AI team is hard. Managing one remotely is even harder. After 7 years of trial and error, here are my most surprising and effective lessons for leading a distributed team of AI experts.
The Reality Nobody Talks About
Most people approach 7 counterintuitive lessons i learned managing a remote 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 simplicity beats complexity every time. 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 you should focus on one thing and do it exceptionally well. Once we made the switch, everything changed.
The Framework That Actually Works
I'm going to share the exact framework I use when evaluating 7 counterintuitive lessons i learned managing a remote. It's not complicated, but it requires discipline.
Step 1: you need to move fast and break things This is where most people go wrong. They skip this step entirely and jump straight to execution. Don't do that.
Step 2: you should focus on one thing and do it exceptionally well 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 in my portfolio that nail 7 counterintuitive lessons i learned managing a remote are the ones that treat it as an ongoing process, not a one-time project.
The AI Angle
I can't talk about 7 counterintuitive lessons i learned managing a remote in 2026 without mentioning AI. As someone who's invested in Anthropic, OpenAI, Scale AI, and Hugging Face, I have a front-row seat to how AI is transforming this space.
The short version: AI makes good practitioners better and bad practitioners worse. It's an amplifier, not a replacement.
I've seen companies use AI to 10x their 7 counterintuitive lessons i learned managing a remote capabilities. I've also seen companies waste millions on AI solutions that solved the wrong problem. The difference comes down to understanding what you're actually trying to achieve.
This connects to broader themes around chief AI officer, AI transformation leadership, AI change management, managing AI teams, AI leadership skills 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 here's the thing about 7 counterintuitive lessons i learned managing a remote: you don't need to get everything right on day one. You just need to get started and keep improving.
The founders in my portfolio who excel at 7 counterintuitive lessons i learned managing a remote 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
Can I implement all of these at once?
I'd strongly recommend against it. Pick the 2-3 items that resonate most with your current situation and focus there. Trying to do everything simultaneously is a recipe for doing nothing well.
How do I know which items apply to my situation?
Start by honestly assessing where your biggest bottleneck is right now. The items that address that specific constraint will give you the highest return on your time and energy.
Which item on this list has the highest impact?
It depends on your stage and context, but in my experience, the items near the top of the list tend to have the broadest applicability. That said, sometimes the less obvious items create the biggest breakthroughs for specific situations.
How were these items selected?
Each item on this list comes from direct experience, either from building my own companies or from patterns I've observed across the 200+ startups I've invested in. I prioritize practical, actionable items over theoretical concepts.