Shipping a language model integration without automated evaluation is flying blind. Manual review does not scale, and eyeballing a handful of outputs in staging misses the regressions that appear after model version bumps or prompt rewrites. This article walks through a practical, layered evaluation framework you can wire into CI.
What "Quality" Means in Practice
Evaluation is context-dependent. For a classification task, quality means accuracy. For a summarizer, it means coverage and faithfulness to the source. For a code generator, it means the output compiles and passes the test suite. Before writing a single line of evaluation code, define your quality dimensions:
Correctness: Does the output contain the expected information?
Format compliance: Is the structure valid JSON, Markdown, or whatever your downstream expects?
