Search for a command to run...
Articles tagged with #evaluation
Your engineering team brings you a number. 87 percent. Is that good? Is it real? Is it better than last week? Is it the number you should care about? Here is the skeptic kit for reading any AI quality report without getting fooled.
Four ways to score an AI output. Each wins on a different problem. Teams that pick the wrong one waste weeks on infrastructure that does not match the quality signal they actually need.
If engineering owns the eval set by default, the eval set will reflect what engineering can measure, not what users actually care about. Here is how a PM builds and keeps control of the artifact that decides shipping.
Your team cannot agree on whether the AI is ready to ship because nobody wrote down what good enough means. Here is the four-part quality bar that replaces the vibes meeting.
The hardest problem in modern AI isn't building the model. It's figuring out whether the model you just built is actually better than the last one. Here's why that's so brutally hard — and what the working state of the art really looks like.
