AI Doesn't Tell Me What's Wrong With Your Team. Your Team Does.
by Chloe Field.
There's a version of the AI conversation that makes me slightly uncomfortable (aside from the AI generated image of myself...)
The one where it's pitched as a shortcut. A way to skip the messy, human part of running a team and jump straight to "optimised."
That's not what we do at re/Work. And honestly, that's not what most early-stage founders need.
What they need is someone to help them see what's actually going on inside their team and how the work actually happens.
So here's how AI actually fits into my work.
I start with people. Every time.
When we work with a team, the first thing we like to do is talk to them. Not just the founder, but with the team.
I want to know what feels hard. What's not working for them? What they wish someone would fix. What they've stopped raising because it never went anywhere.
We might start by profiling the team's motives, strengths and gaps. We look at habits and rituals. What feels slow? What's working vs not working? How do they feel about their priorities, etc.?
Every person on a team is carrying a piece of the puzzle. The problem is that no one person (including the founder) is holding it all.
It's usually a combination of:
People are doing the right work, but in different ways
Feedback happens, but it's scattered across channels and meetings
Leaders think they understand the friction points, but they're hearing it through whispers
Everyone's carrying a signal 💡
That's the gap I like trying to understand (and close!).
Then AI comes in.
I don't use AI to tell me what's wrong. The founder and team already told me that.
I use it to sit with everything I've heard and make sure I'm not missing anything, not as a decider but as a pattern mirror.
I need it to catch patterns, because I might skim over what three people said differently and to challenge my own bias before I walk back into a room and say "okay, here's what I'm seeing."
I use it to synthesise themes across roles and teams, surface contradictions leadership might miss, highlight where process clashes with human behaviour and stress-test assumptions before I codify anything.
It's a sense check. Not the source of truth, just something that helps me get the full picture.
Why does this matter?
Most people advice fails because it starts with a template. And templates assume every team is the same. And every company is the same.
Spoiler alert...they're not.
I like to think of each company I work with as its own organism. Patterns will be similar across these different organisms, but they are also incredibly unique. A workflow that works beautifully for one team might not work for another. The way a team of 6 at a creative agency communicates is completely different to that of a 20 person scaleup.
What we care about is how this team actually works. How this founder makes decisions. What these people can realistically execute right now.
So the system fits the humans. Not the other way around.
That's the difference between something that looks good on paper and something people actually follow. It comes down to experience, good judgement and context.
The takeaway is simple.
AI is useful when it helps you listen better. It's not good when it lets you skip listening altogether.
AI is such a powerful tool that helps you amplify insight; it doesn't replace the human understanding that actually matters.
The founders who build great teams over the next few years won't be the ones who automate the most or move the fastest. It'll be the ones who understand their people clearly enough to know what actually needs to change and what just needs to be understood.
That's the real work.