Output Validation
Also called Output Validation
Checking what the model produced before you actually use it — for format, safety, and sanity.
Think of it like
Proofreading a letter before mailing it, not after — catching the typo while you still can.
Example
A model returns JSON for an app; a validator confirms it parses and matches the schema, and if not, asks the model to fix it rather than crashing downstream.
How it actually works
Models produce plausible text, not guaranteed-correct or guaranteed-safe text, so a robust system doesn’t trust the raw output. Output validation runs checks after generation: schema and format checks, safety classifiers, grounding checks against sources, business-rule checks. Failures can be blocked, retried, or repaired. It’s the last line before output becomes action — especially important once an agent can trigger real side effects.
For product teams
The safety net that turns "the model usually gets it right" into something you can actually build on.
For engineers
Post-generation checks (schema, safety, grounding, rules) with block/retry/repair handling; essential before outputs drive side effects.
Related
- Grounding Check — A specific grounding check on outputs.
- Content Filter — The filter layer it often includes.
- Indirect Prompt Injection — Limits the damage from injected instructions.
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