The first time I spent an entire afternoon working with AI, I closed my laptop with that strangely satisfying feeling of having done hard intellectual work. My brain felt cooked. I had compared models, refined prompts, rewritten outputs, tested workflows, chased better phrasing, discarded entire approaches. It felt intense. Dense. Productive.
A few years ago, I contributed an essay to a book about running. It was called Die Philosophie des Laufens (The Philosophie of Running) and published by Mairisch, a small independent press with excellent taste and the kind of literary courage that larger houses often like to claim for themselves.
A few weeks ago, I posted on LinkedIn that my current role is coming to an end and that I’m exploring what’s next. The response was generous. Messages. Comments. Encouragement. The kind of digital warmth that makes you believe platforms can still be relational spaces. And then, as always, the curve flattened. Which is normal. Attention spikes and fades. That’s how feeds work.
»I tend to think that most fears about A.I. are best understood as fears about capitalism.« When I read that line from Ted Chiang recently, it landed because it pulls the mask off the monster. A lot of what we call »fear of AI« is really fear of incentives: who funds the systems, who deploys them, who benefits when they scale, and who gets hurt when they fail.
There’s something mildly absurd about modern running tech. Every brand talks about AI now. Smart coaching, predictive training plans, readiness scores, recovery scores, stress scores, you name it. My watch apparently knows my future. It just doesn’t know what happened five minutes ago.