interview

To extract detailed software requirements without writing a full spec upfront, you can use a reverse-interview process where an AI asks targeted questions to define technical decisions, edge cases, and scope for your development tasks.

The best way to gather user stories and specifications for a new codebase feature is to conduct a multi-round interview that scans your codebase context first, then asks targeted questions to elicit detailed requirements based on the existing code.

Code analysis improves the requirements gathering process by scanning the codebase to inform the interview questions, ensuring the generated specifications and user stories are accurately grounded in your existing technical context and architecture.

Yes, you can generate a structured markdown specification file directly from a requirements interview, which outputs a `specs/{topic-slug}.md` file containing clearly defined requirements, technical decisions, and edge cases.

Yes, automated requirements gathering works for defining edge cases and project scope by conducting a structured, multi-round interview that specifically prompts you to address technical decisions and boundary conditions you might otherwise overlook.

The limitation of using an AI interview for software documentation is that the output quality depends entirely on your engagement during the multi-round process; it facilitates the extraction of specifications but requires your active input to define accurate requirements.