Guardrails for
test case generation.
A validation layer for an LLM-based test generation system — checking outputs against schema, coverage, and safety constraints before they reach engineers.
Generated tests looked right, but weren't always right.
[The gap: LLMs produced syntactically valid test cases that sometimes missed coverage requirements, used hallucinated APIs, or violated safety rules. Engineers couldn't trust the output without re-reading every case, which defeated the point.]
Validate before the engineer ever sees it.
[The layers: schema validation against the test framework, coverage checks against the spec, safety filters for sensitive patterns, and a fallback path when generation fails the bar. Each layer rejects or repairs before output reaches the user.]
Engineers started shipping the AI's tests.
[Outcomes: trust went up, review time went down, adoption became real. The number that matters most is whichever you can share — fewer rejected tests, faster iteration, more cases shipped without rewrite.]
The model isn't the product — the system around it is.
[Reflection: a great LLM with no guardrails is a demo. A modest LLM with strong guardrails is a tool. Most of the work was in the layer that decided what counted as "good enough to ship."]