Evaluation Overview

This chapter introduces the benchmarks, metrics, and evaluation frameworks commonly used to assess LLMs and agent systems. The goal is to compare models reliably, catch failures early, and make iteration faster.

What this chapter covers

• Benchmarks: datasets and task suites used to track progress.

• Metrics: automatic, human, and judge-based scoring signals.

• Frameworks: tooling that standardizes grading and reporting.

Together, these pieces turn evaluation from ad-hoc testing into a repeatable process.