They are not.
Evals help you answer: “Does the model behave as expected on the cases we care about?”
Product QA helps you answer: “Does the product behave safely and correctly when real users are messy, and when tool calls and permissions are in play?”
One passes, the other fails (a quick reality check)
Evals pass, product fails
The model gives good answers in the eval harness.
In production:
- a tool call path bypasses an approval gate
- a timeout fallback shows the wrong UX
- an edge permission path leaks context or blocks incorrectly
The system glue failed. Evals did not test glue.
Product QA passes, evals fail
The UI does not crash.
In production:
- structured outputs are sometimes invalid
- grounding fails on retrieval misses
- the model guesses confidently when it should refuse
The system runs, but answer quality and safety degrade.
The combining move
Pick release criteria you can explain:
- Model layer: correctness, refusal, grounding, structured output validity
- Product layer: permissions, tool safety, fallback UX, failure handling
Then severity-rank what you find and decide ship / wait / block.
If you want the full combined release sequence, read the guide:
And if you are days from launch and need help turning “green evals” into a real release gate, book a free triage.