September 2026
Intermediate
216 pages
5h 33m
English
Content preview from AI Evals in Practice
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Chapter 4 — Deterministic Scorers
Before you spend a dollar on an LLM-as-judge call, ask yourself: can a simple function answer the question? You would be surprised how often the answer is yes.
Deterministic scorers are functions that evaluate output quality without calling any LLM. They are free, fast (microseconds per call), perfectly reproducible, and can run on every single request in production. They form the base layer of any eval system — the checks that catch obvious problems before the more expensive, sophisticated scorers even need to run.
In chapter 2, we built ExactMatch, Contains, and RegexMatch. In chapter 3, we added ContainsAll and JsonMatch. In this chapter, we complete the deterministic scorer suite: embedding similarity, JSON ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.