Letting go is how you keep up

Crab Week, our company offsite in Šibenik, Croatia. We were standing near the hotel lobby talking about AI. I showed them Paperclip, a tool I've been building with. One agent delegating work to a dozen others, creating PRs while we watched. Nobody said anything. I'd been expecting questions. How does it handle errors. How do you keep the agents focused. We moved on, talked about other things. But what I kept thinking was: how do I get them to see what this could do for them, not to them.

Most people think AI threatens jobs. More often, it threatens identities.

In the days after, I kept having similar conversations. A colleague told me they were thinking about leaving for an AI-native company before they miss the boat. I thought they might be right. We’re not moving fast enough. But they weren’t really chasing speed. They knew they had to reinvent, and didn’t think they could do it here. They wanted to be somewhere figuring out what work actually becomes.

Managers know this feeling

I've been struggling with this for years.

It reminds me of when I became a manager. You get promoted because you're good at the work. Then you're supposed to stop doing it. Except you're also the one who knows why it works in the first place, and that doesn't transfer in a handover doc.

Our data platform team is four people. I still fix things at odd hours that I should be delegating. It's faster, I know the code, and I tell myself I'm just unblocking the team.

That's the tension. Let go and you lose touch. Hold on and you become the bottleneck.

AI just did this to everyone at once. And now everyone's asking the same question managers have been asking for years: if I'm not the one doing the work, what am I?

So I made my team try it

I was doubting all week whether I should have the team try it. But after all the hype during our offsite about practical use of AI, it felt right. They needed to see Paperclip for themselves.

Four data and analytics engineers, each managing their own agents. Within an hour they'd hired a dozen agents and couldn't get them to work together. One person wanted more governance. Another wanted to move faster and hire more. They clashed. They ended up acting as a board of directors, arguing about the goals of their company.

Nobody was writing SQL. Everyone was managing. The agents kept going, PRs kept getting created, needing more guidance than anyone expected. My team was the bottleneck for direction and quality control. The agents didn't have enough of our tribal knowledge, the same way a new hire doesn't.

I let it sit for a while after that. Let them think about what they'd just experienced. We're not going all in overnight. Though we already have an agent triaging data issues from our observability tool, freeing us up to focus on what actually needs us.

The impossible balance

I've always identified with getting things done fast. I still do. AI makes me even faster.

But that's also the trap.

If I only use it to move faster myself, nothing really changes. I'm still the bottleneck. Just a faster one.

The harder part is getting the team there too.

That means letting go of the parts of the job that feel safest. Writing the query. Fixing the issue. Knowing the code path. Being the person who can always make it work.

Those things still matter. But they can't be the whole job anymore.

In the Paperclip exercise, the team didn't need to write more SQL. They needed to decide what the agents were trying to do, what good looked like, where to slow down, and when to stop.

That's the part I'm still figuring out.

You can find Paperclip on GitHub