Code Review, Part 2: The Reviewer That Learned To Lie Better Several posts ago, I wrote about setting up a multi-agent adversarial code review process as part of my development pipeline. The premise came from a podcast: if one frontier model is writing the code, you want a different lineage model doing the review. I'd already been running
Non-determinism is the job Early in my career, and partially because I worked at a place that was a little silly and I didn't have much contact outside the organization, my title in my email signature was Spaghetti Straightener / Cat Herder. The first part was a nod to the code I was
The Finding Nobody Implemented The DORA research said culture predicts engineering performance. Nicole Forsgren's most important finding never made it into a single commercial product. As a computer scientist, I love data. Things feel good, things feel bad, but our biases shape those feelings, and data is what pulls the signal out.
Debugging Predictability at the Team Level What the numbers are trying to tell you, and how to get them to say it out loud. In the last post I wrote about what predictability is and what it actually measures. This one is about what to do when the number looks wrong. When I first started using
What predictability actually measures (and why velocity is the wrong question) Why I invented a metric I'd never heard of, and why the industry eventually caught up. I started using the term "predictability" in 2019, and I was pretty sure I was making it up. The situation that produced it was not subtle. I had just taken
I Can't Tell If the Model Matters What I actually found when I set out to test heterogeneous AI code review. For the last couple of months, I've been running a two-agent code review workflow in my terminal. Left window: Claude Code doing implementation. Right window: a second Claude Code instance prompted to be
Priority Inversion: The Bug Triage Failure Nobody Talks About Why your team is probably working on the wrong bugs, and why they don't know it.
engineering-leadership How I Assess Engineering Health in My First Week at a New Org The diagnostic framework I run every time I join a new engineering organization, and why the data is only half the picture.
Okay, But I'm Still Using It Where I'm actually deploying AI coding tools at my next organization, and why. If you read my last post, you know I'm not a believer in the uncritical sense. Context rot is real. The confidence-to-accuracy gap is real. The autonomous decision-making that nobody
I Can't Tell If You're Selling Me Something What I actually found when I stopped reading about AI and started running my own experiments.
