AI Evals & LLM-as-Judge
Build repeatable evaluation practices for AI features — from hand-labeled test sets to automated LLM-as-judge grading — so quality is measured, not assumed.
A demo that looks good is not a quality process. These lessons cover building real eval sets, choosing the right kind of metric for a task, using an LLM as a judge without being misled by it, and wiring evals into how you actually ship changes.
Why AI Products Need Evals
Understand why 'it looks good in the demo' is not a quality process, and what an eval set actually is.
7 min read →Designing Metrics: Exact Checks, Rubrics, and Reference Answers
Learn how to choose the right kind of check for different types of AI output, from deterministic validation to human rubrics.
7 min read →Using an LLM as a Judge
Learn when and how to use a model to grade another model's output at scale, and the failure modes to guard against.
7 min read →Wiring Evals Into Development and Deployment
Learn how to make evals a routine part of shipping AI features rather than a one-time exercise.
7 min read →