Pre-Discovery with Subagents

For features spanning multiple domains (auth, database, UI, etc.) that need front-loaded technical context before the Feature Forge interview.

Overview

For features spanning multiple domains, you can accelerate discovery by launching Task subagents with relevant skills BEFORE starting the Feature Forge interview. This front-loads technical context so the interview focuses on decisions rather than exploration.

When to Use

• Feature touches 3+ distinct system layers (e.g., auth, database, UI)
• Codebase is unfamiliar or underdocumented
• You need concrete technical facts before asking requirements questions
• Stakeholder time is limited and you want to minimize back-and-forth

When NOT to Use

• Feature is well-scoped to a single domain
• You already have deep codebase knowledge
• Requirements are purely business/UX (no technical exploration needed)

Pattern

1. Identify domains the feature touches
2. Launch parallel Task subagents with relevant skills:
   - Architecture Designer → existing patterns and constraints
   - Framework Expert → current implementation details
   - Security Reviewer → security requirements and risks
3. Collect findings from all subagents
4. Begin Feature Forge interview with technical context loaded
5. Focus interview on decisions, trade-offs, and requirements

Example

For a "user profile with avatar upload" feature:

Task subagent 1 (Architecture Designer):
  "Analyze the current user model, storage patterns, and image handling in this codebase"

Task subagent 2 (Security Reviewer):
  "What security concerns exist for file upload in this stack?"

Task subagent 3 (Framework Expert):
  "How does this project handle API endpoints and file storage?"

Results feed into the Feature Forge interview, so questions like "Where should we store avatars?" come with context about existing patterns.

Integration with Interview Questions

See interview-questions.md for the full multi-agent discovery pattern and how subagent findings map to interview categories.