honcho-interview

To save cross-project user preferences, you can run an interactive session that captures communication style, collaboration preferences, and tooling choices into persistent memory. The session batches remaining preference questions into a single list for you to answer once and move on.

Memory-first interviewing avoids repeating known user preferences by checking existing memory and scanning environment files before asking any questions. It identifies your saved communication style and technical depth, then only presents a batched list of remaining unknown preferences.

The best way to record developer onboarding preferences is to run an interactive interview that scans your environment and saves code-quality priorities, package managers, and editor tooling. It generates single-sentence conclusions for reliable future behavior across sessions.

Yes, you can use environment scans to detect your development tooling and save it to memory. The interview process automatically performs an environment scan to collect your current package managers, editors, and tooling choices before generating structured conclusions.

You need to generate single-sentence conclusions for user preferences when you want to reliably save them to memory for consistent future behavior. Each clear preference identified during the interactive interview is converted into a distinct conclusion suitable for memory storage.

Yes, the preference interview works across different projects and context wipes by capturing stable, cross-project preferences into persistent memory. This ensures the AI assistant can remember and apply consistent behavior regardless of session resets or project switches.