Regression CI for RAG and agents

Integrating non-deterministic validation gates directly into automated deployment pipelines.

Why it matters

Treat AI quality gates exactly like traditional code unit tests. By executing your evaluation suite within a CI/CD pipeline, any subtle degradation in context precision or spike in hallucination rates automatically breaks the build, preventing faulty prompts or unverified model bumps from reaching production.

Treat AI quality like unit tests: run the golden set in CI and fail the build when quality drops. Without a gate, a prompt tweak or a model-version bump silently degrades production.

rag_ci_gate:
  dataset: golden/refund-v3.jsonl
  thresholds: { recall_at_5: '>= 0.85', faithfulness: '>= 0.92', p95_latency_ms: '<= 1800' }
  fail_build_on:
    - recall_at_5 drops by more than 0.03
    - any P0 safety case fails

Declare what actually fails the build. A dashboard that shows a regression but doesn't block the deploy is decoration. The gate must name concrete conditions (absolute thresholds and delta-from-baseline) and a rollback action, or the regression ships and someone notices in production a week later.

Every threshold needs an owner. An unowned metric is informational only — when it fails, nobody is accountable to fix or waive it, so teams quietly start ignoring red. Assigning an owner per threshold is what keeps the gate meaningful.

Handle judge flakiness statistically. LLM-as-judge scores wobble run-to-run. Use multiple samples and a variance bound so the build fails on real drops, not noise — otherwise flaky red trains the team to bypass the gate, which is worse than having no gate.

Regression CI is a circuit breaker, not a warning light. A warning light lets you keep driving toward the cliff; the breaker physically cuts power when current spikes. A quality gate that only logs is a warning light — make it trip the deploy.

• Dashboards without gates. Symptom: regressions ship. Fix: hard fail conditions in CI.
• Unowned thresholds. Symptom: red gets ignored. Fix: an owner per metric.
• No statistical guardrail. Symptom: flaky red, gate bypassed. Fix: multi-sample + variance bounds.
• No rollback action. Fix: define the automatic rollback on failure.