Six failure cases to test before shipping an AI workflow

Short summary

A practical tutorial defining six acceptance tests every AI workflow should pass before shipping: valid input handling, retry idempotency, dependency failure recording, enforced human approval gates, evidence-based completion validation, and malformed input rejection. The author provides a five-field contract template (workflow name, outcome, approval point, side effect, evidence reference) and a JSON run-log schema. The approach is model-agnostic and applies to OCR flows, support agents, API automations, or research assistants.

• •Six acceptance tests: malformed input, duplicate delivery, dependency failure, missing approval, missing evidence, happy path
• •Completion rule requires outcome observed + evidence exists + approval granted + zero duplicate side effects
• •Includes a JSON run-log validator schema and a no-login browser tool for contract editing

Generated with AI, which can make mistakes.