Bottleneck Resolution is, In Fact, All the Rage in AI Engineering

The AI Engineer World's Fair here in San Francisco is fundamentally a conference for practitioners — devs who need to be productive today. While it naturally attracts folks operating on the absolute cutting edge, at the end of the day, most of us are just developers trying to ship. I touched on this in my observations yesterday.

Before arriving, I wrote abstractly about navigating unavoidable bottlenecks in an era of infinite code. This week, I'm seeing that theory play out in real time across the keynotes. This morning, OpenClaw creator Peter Steinberger took the stage to talk about bottlenecks in a deeply pragmatic way. The AI space is inherently glitzy, but the dialogue is finally grounding itself in the messy, practical in-between parts where things actually get done.

Bottleneck resolution is boring, but it's good boring. I don't need keynotes that promise a future where friction magically vanishes; I want the patterns and engineering discipline required to solve the constraints we have right now. It's the exact same thing we've always wanted from traditional software eras — and it's exactly where we've arrived with AI.