Vibe Coding
Vibe Coding builds software through conversation. A person sets and checks the goal while an AI agent writes much of the code.
Another example
A founder describes an invoice reminder and lets an agent prototype it. They test real flows, clarify success rules, review the diff, and reject unsafe shortcuts.
Main parts
- 01User intent and context
- 02Model or tool decision
- 03Grounded result and fallback
Use it when
Use it to explore quickly when a person can inspect changes and test according to risk.
Do not use it when
Do not ship unseen changes, give up product judgment, expose credentials, or mistake fluent output for sound design.
Name used in code
intent → agent change → inspect → test → refine Before you ship
Check the model and prompt versions, source data, versioned evaluation set, and measures. Verify links to evidence, tool permissions, privacy, common failures, decline-to-answer and fallback behavior, human review, monitoring, cost, speed, and rollback.
Outcome: Use or evaluate Vibe Coding to make AI behavior measurable and tied to evidence. User context: A founder describes an invoice reminder and lets an agent prototype it. They test real flows, clarify success rules, review the diff, and reject unsafe shortcuts. AI method or concept: Vibe Coding. Why it fits: Use it to explore quickly when a person can inspect changes and test according to risk. Do not use it when: Do not ship unseen changes, give up product judgment, expose credentials, or mistake fluent output for sound design. AI requirements: Define the input and source evidence. Set model and tool permissions. Use versioned evaluation data and measures. Define failure, decline-to-answer, privacy, speed, and cost limits. Operational safeguards: Keep a clear trace and hide sensitive log data. Show users a safe fallback. Mark steps that need human review. Define how to roll back the model or prompt. Acceptance criteria: Record baseline and target measures on a versioned evaluation set. Test edge cases and hostile inputs. Verify fallback, monitoring, permissions, and rollback. Evidence and limits (evidence boundary): This is not a normative standard. Its name, limits, and expected behavior can change from one source to another. Unknowns to confirm: Target task, model and version, evaluation owner, source data, risk limit, tool permissions, and production fallback.
Check this request
Review the current use of Vibe Coding. Definition: Vibe Coding builds software through conversation. A person sets and checks the goal while an AI agent writes much of the code. Release checks: Check the model and prompt versions, source data, versioned evaluation set, and measures. Verify links to evidence, tool permissions, privacy, common failures, decline-to-answer and fallback behavior, human review, monitoring, cost, speed, and rollback. Before changing code, report the evidence you found, gaps, severity, and the smallest safe fix.