How Evals and Prompts Shape Agent Behavior — Preetika Bhateja & Daniel Bump, YouTube Ads
Source
AI Engineer
Author
AI Engineer
Date
Terms in this piece · Glossary
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
eval — A repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.
Why it matters
evalA repeatable test for AI quality — a set of tasks plus scoring — used the way software teams use test suites, because model output is too variable to judge by eyeballing.Full definition →-driven iteration is the part of AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → development most teams skip, and this shows what it looks like in production.
Key quotes
“Checking if the model like didn't do something as bad, uh, something bad is just as critical as checking if it did the task.”
Daniel Bump
“writing the evals can be a very small point and humans arguing over what the rubric should be is, uh, is kind of like a very large task here”
Daniel Bump
“I found a disclaimer and now I'm going to go ahead and remove it, which was not what we asked it to do.”
Preetika Bhateja
“if you do this, this is kind of a trap because as I said before, these are non-deterministic systems. So what's more important is that you actually rely on patterns.”
Daniel Bump
“what we think makes a good eval system generally is like it should be representative of what you want your product to be great at.”
