When AI Starts Writing Your System, Who Tells It What 'Done' Means?

说明与用途

使用本地、版本控制的 OpenAPI 规范作为唯一的真相来源，使 AI 生成的代码与人类期望保持一致，减少集成错误，并创建早期捕获缺口的反馈循环。

问题

AI-generated code can diverge on shared definitions, causing inconsistent behavior such as duplicate bookings and status mismatches.

结果

Using a local, version-controlled OAS as the single source of truth aligns AI-generated code with human expectations, reduces integration bugs, and creates a feedback loop that catches gaps early.

工作流

• 1. Define business request and ask AI to propose design against existing OAS.
• 2. Review AI’s suggested changes to endpoints, schemas, and rules.
• 3. Apply approved changes to local OAS file and commit to version control.
• 4. Use the OAS as input for coding assistants and mock services during implementation.
• 5. Run contract checks and scenario tests against the spec to verify real requests.
• 6. Iterate based on mismatches or missing fields, updating the OAS accordingly.
• 7. Render documentation and publish MCP endpoints from the same OAS file.

证据

An OpenAPI Specification (OAS) describes endpoints, parameters, responses, and auth in a structured format.

来源

In Powerduck, you start from a business request and ask the AI to propose a design against the existing spec.

来源

The OAS does not have to stop at "design output." In a Powerduck workflow, it continues to feed the later stages: Design, Implementation, Waiting on dependencies, Verification, Delivery.

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The spec lives as a local file. It goes into version control, code review, and rollback alongside the code.

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