Abstract
Code review was built for a world where humans wrote all the code. The question shifts from "does this diff look good?" to "can this system safely ship code on its own?" Shows how traditional code review gets quietly replaced by automated verification harnesses, how prompt learning clones your best internal reviewers into automated evaluation loops, and open-sources a code review training harness that turns review patterns into reusable checks for AI-generated code.
Interview:
What is your session about, and why is it important for senior software developers?
Everybody has started using LLM assistance to generate code, and that has eliminated the speed of coding as a bottleneck, but revealed a new one: the speed of reviewing the code we produce, to make sure it's correct and safe. My talk is about the current state of the art in accelerated code review.
Why is it critical for software leaders to focus on this topic right now?
Data shows that coders using LLM assistance wrote more than 700% more code but released only 30% more actual software; that gap is all about the bottleneck of review.
What are the common challenges developers and architects face in this area?
The whole space is brand new. Nobody's really sure what works and what doesn't. Can we automate review? Can we eliminate review? Can we avoid review with better specs? People are trying all sorts of strategies.
What's one thing you hope attendees will implement immediately after your talk?
That while this is an unsolved problem, there are better strategies out there than just "review faster", which demonstrably doesn't work.
Speaker
Laurie Voss
Head of Developer Relations @Arize AI, Co-Founder of npm, Inc., Developer for 30+ Years
Laurie Voss is Head of Developer Relations at Arize AI, the leading company for AI observability and evaluations. He has been a developer for over 30 years and was co-founder of npm, Inc.. He believes passionately in making the web bigger, better, and more accessible for everyone.
