AI evaluation consultant Hamel Husain explains why teams fail at AI evals when they skip manual trace inspection and error categorization.
Insight
Husain: Coding agents differ from other AI products because devs dogfood them
“Coding agents are fundamentally very different than other AI products because the developer is the domain expert. So you can short circuit a lot of things, and also the developer is using it all day long.”
Insight
Husain: General LLM benchmarks do not correlate with product-specific evals
“Up until now, a lot of the big labs understandably focused on general benchmarks, like MMLU score, human eval, things like that, which are very important for foundation models. And, you know, those not very related to product specific evals, like the ones we t…”
Opinion
Husain: Product managers, not developers, must lead AI trace error analysis
“Product people have to be in the room and they have to be involved in sort of doing this. You know, usually a developer is not suited to do this, especially if it's not a coding application.”
Insight
Husain: LLM-as-a-judge evaluators must use binary scores instead of 1-5 scales
“When you go to building an LLM as a judge, you need a binary score. You don't want to think about, is this like a one, two, three, four, five, like assign a score to it. You can't, that's going to slow it down.”
Insight
Husain: Prioritize code-based evals over LLM judges to save cost and complexity
“So there's different kinds of evals. One is code-based, which you should try to do if you can, because they're cheaper. You don't have to, you know, LLM as a judge is something, it's like a meta eval. You have to eval that eval to make sure the LLM that's judg…”
Opinion
Husain: Buying off-the-shelf automated AI eval tools does not work
“The top one is, hey, I can just buy a tool, plug it in, and it'll do the eval for you. Why do I have to worry about this? We live in the age of AI. Can't the AI just eval it? That's the most common misconception. And people want that so much that people do sel…”