LLM Testing, Regression, and Benchmarking

LLM Testing Needs More Than Unit Tests

AI application behavior depends on prompts, models, retrieval context, tool schemas, policies, and user inputs. Regression testing helps teams detect when a change improves one path but breaks another.

Testing Practices

• Version prompts, schemas, model settings, and retrieval configuration.
• Use test cases for common tasks, edge cases, and adversarial inputs.
• Compare outputs across model versions and prompt revisions.
• Track pass/fail metrics, human review scores, latency, and cost.
• Use release gates for safety-critical or customer-facing workflows.

Benchmark Against Your Product

General benchmarks are useful, but product-specific regression suites are more important for production reliability. Test the workflows your users actually run.