Jeremy Meiss

We’ve all seen the demos where an AI writes a “To-Do” app in thirty seconds. It’s impressive, sure, in the same way a dog riding a bicycle is impressive - but it’s not exactly how we build production-grade software. In the real world the SDLC is messy, our pipelines are held together by legacy YAML, and “moving fast” usually means “breaking things we didn’t know existed.”

This talk looks past the hype and into the data: DORA, CircleCI, Sonar, and METR’s own randomized controlled trial, plus what happened when Meta, Uber, and Amazon took agentic AI further than almost anyone else this year. AI is an amplifier - it makes strong teams stronger and struggling teams worse, faster. The question isn’t what AI can build. It’s how you ship this without making everyone furious.

At the end, we’ll have a roadmap: what to measure, what to budget for, and why the most important part of AI-driven DevOps isn’t the code it generates, but the bottlenecks it actually clears.