Evals that gate releases
Evals only matter when something is blocked by them. The goal is a suite that runs in CI, has a threshold, and stops a release when the threshold is missed.
What is LLM evals in CI?
Evals only matter when something is blocked by them. The goal is a suite that runs in CI, has a threshold, and stops a release when the threshold is missed.
Implementation
- Freeze a golden suite of tasks drawn from real workflows, with expected outputs reviewed by a human once.
- Run the suite in its own CI workflow, separate from unit tests, so a slow eval does not block ordinary commits.
- Add adversarial cases: prompt injection, contradictory instructions, missing tools, truncated context.
- Record per-task cost and latency alongside pass/fail so a regression in spend is visible.
- Set an explicit threshold and fail the workflow below it.
Failure modes
- Suites that only contain cases the system already passes.
- Thresholds nobody enforces.
- Golden outputs updated to match new behaviour without review, which quietly ratifies a regression.
How it is verified
- Introduce a known-bad change and confirm the eval workflow fails.
- Check that the run cost is recorded per task and trending.
Questions this pattern answers
What is LLM evals in CI?
Evals only matter when something is blocked by them. The goal is a suite that runs in CI, has a threshold, and stops a release when the threshold is missed.
How do you implement evals that gate releases?
Freeze a golden suite of tasks drawn from real workflows, with expected outputs reviewed by a human once. Run the suite in its own CI workflow, separate from unit tests, so a slow eval does not block ordinary commits. Add adversarial cases: prompt injection, contradictory instructions, missing tools, truncated context. Record per-task cost and latency alongside pass/fail so a regression in spend is visible. Set an explicit threshold and fail the workflow below it.
How is evals that gate releases verified?
Introduce a known-bad change and confirm the eval workflow fails. Check that the run cost is recorded per task and trending.
What usually goes wrong with evals that gate releases?
Suites that only contain cases the system already passes. Thresholds nobody enforces. Golden outputs updated to match new behaviour without review, which quietly ratifies a regression.
Projects in this track
ClawKeeper →
Governed Claude agent control plane. A deterministic policy engine runs before every LLM call, autonomous spend defaults to zero, and the audit log is enforced by the database.
TechTide Harness Kit →
Trust contracts for agent skills expressed as JSON Schema: risk tiers, tool permissions, deny-by-default egress, approval gates, and prompt-injection fixtures behind a wall of CI validation gates.
CipherClaw →
Deterministic multi-agent debugger with zero LLM calls in the analysis path: causal graphs, weighted root-cause scoring, and failure prediction.
Swarm 357 →
357 Claude agent roles across six business layers, with portable memory, enforced cost caps, a bash policy gate, and durable checkpoints.
Related patterns
This page documents how the pattern is built. Engagement scope and pricing live on TechTide AI.
AI Production Systems at TechTide AI→© 2026 Alex Cinovoj · TechTide AI · Columbus, OH