News, engineering deep dives, and tutorials from the Pipelines team.
Evaluating an agent is not the same problem as evaluating a model's output. One is a fixed input-output mapping; the other is behavior that emerges from interaction with an environment that responds. Most tooling solves the first problem — agents pose the second.
Everyone agrees AI needs better evaluation. But what does that mean in practice? Here's the anatomy of an evaluation system designed for reproducibility, not just vibes.
Your team made a hundred model and prompt decisions in the last six months. How many can you defend with data? Rigor isn't about slowing down -- it's about building a foundation your team can actually stand on.