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How do I validate AI outputs automatically?

Use schemas, regexes, and business rules to check structure and plausibility. For text, verify presence of required sections; for numbers, enforce ranges and reconciliations. Add a second model or the same model in ‘critic’ mode to review outputs. If validation fails, retry with a targeted correction prompt.

In practice

Keep validators deterministic and simple; write them before you ship the prompt.

Where to start

  1. [01]Define a schema or regex for outputs.
  2. [02]Write a validator function with clear errors.
  3. [03]Add an auto-retry with specific correction hints.
  4. [04]Log failure reasons to guide prompt changes.
output validationAI guardrailsprompt validation

Related questions

// 001How do I prevent repetitive outputs across runs?// 002What’s a good fallback strategy when a prompt fails?// 003Which analytics matter for prompts in production?// 004How do I improve internal search with prompt engineering?

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Open source · Python