Quick Answer
Making evals real means integrating them into the product lifecycle: release gates, drift monitoring, human escalation, and feedback loops.
TL;DR
- Automate evals in CI/CD and block regressions.
- Monitor live drift and human escalations.
- Continuously refresh data and rubrics.
FAQ
How do I prevent alert fatigue?
Use severity tiers, rate limits, and only alert on changes that require action.
What belongs in a release gate?
High-risk KPIs like critical hallucination rate, policy adherence, and security constraints.
How do I scale evals?
Prioritize the top-risk workflows, then expand with automation and targeted golden sets.
The Golden Rules
- Do version your Golden Dataset. Evals are useless if the target keeps moving secretly.
- Do include negative tests. Ensure your model knows when to say "I don't know."
- Don't trust "Vibes". Always quantify. "It feels better" is not a metric.
- Don't run evals on training data. This is just testing memorization, not reasoning.