This is one of the most important pieces of writing I’ve read on AI – and that’s not the kind of thing I say lightly. If you’re leading in a business right now and looking at AI adoption, it’s worth your full attention.

Duncan Brown’s Team dynamics after AI isn’t about model performance or the usual surface-level debates. It’s about the potential for AI to quietly reshape the structure and dynamics of teams – how work actually gets done.

He shows how the promise of AI enabling smaller teams (“small giants”) and individuals taking on hybrid roles can lead organisations to blur boundaries, remove friction and assume they can do more with less. But when that happens, you lose the feedback loops, diversity of perspective – and start to erode the structural foundations that quietly hold alignment together and make teams effective.

He also points to something I’ve been saying for a while – that AI doesn’t necessarily make us more productive, it can just make us busier. More output, more artefacts, more noise – but not always more value.

Here lies the organisational risk. The system starts to drift. Decisions narrow. Learning slows. More artefacts get produced, but they create more coordination and interpretation work, not less. The subtle structures that keep context and coherence together begin to thin out. Everything looks efficient – right up until it isn’t.

A bit like what happened with Nike: they optimised for the short-term and de-emphasised the harder, slower work that built long-term brand strength. It seemed to work at first, but the damage wasn’t visible until it was too late and it’ll now take them years to build back.

It’s also written by someone who’s been deep in the trenches – leading engineering at the UK Gov’s AI incubator, so not your usual ill-informed AI commentator.

And as a massive Ian MacKaye/Fugazi fan and a lapsed skateboarder, it honestly feels like another me wrote it.

Essential reading. It’s a long read – get a brew and a quiet 15 minutes.