Why AI Feature Design Should Start With Failure Modes, Not the Happy Path

Software engineers building AI-powered features are advised to map out failure scenarios before writing a single line of implementation code. A failure-mode table — covering timeouts, retrieval misses, malformed outputs, and ambiguous writes — should shape the API contract, control flow, telemetry, and tests from the start. Using a support-ticket reply feature as an example, the approach highlights how questions like duplicate drafts from retries or unconfirmed saves are part of the feature contract, not afterthoughts. Unacceptable outcomes, such as replies drawn from another tenant's data or drafts saved without a confirmed write, are argued to be more actionable design constraints than vague goals like 'handle errors gracefully.' The core argument is that postponing these decisions until implementation means the answers end up being whatever an exception handler or SDK default happens to produce.