Interview Questions
PM Hat Questions
Focus on user value and business goals.
| Area | Questions |
|---|---|
| Problem | What problem does this solve? Who experiences this problem? How often? |
| Users | Who are the target users? What are their goals? Technical level? |
| Value | How will users benefit? What's the business value? ROI? |
| Scope | What's in scope? What's explicitly out of scope? MVP vs full version? |
| Success | How will we measure success? Key metrics? |
| Priority | Is this a must-have, should-have, or nice-to-have? |
Example PM Questions
For a "User Export" feature:
- Who needs to export data and why?
- What format do they need (CSV, JSON, Excel)?
- How much data? 100 rows or 1 million?
- Is this for compliance (GDPR) or convenience?
- How often will this be used?
- What's the deadline?Dev Hat Questions
Focus on technical feasibility and edge cases.
| Area | Questions |
|---|---|
| Integration | What systems does this touch? APIs, databases, services? |
| Security | Authentication required? Data sensitivity (PII, PCI)? |
| Performance | Expected load? Response time requirements? Async OK? |
| Edge Cases | What happens when X fails? Empty states? Limits? |
| Data | What's stored? Retention period? Backup needs? |
| Dependencies | External services? Rate limits? Costs? |
Example Dev Questions
For a "User Export" feature:
- What fields to include? Are any sensitive (passwords, tokens)?
- Max export size? Need streaming or background job?
- Should include soft-deleted records?
- What happens if export fails midway?
- File retention - how long to keep generated files?
- Need progress indicator for large exports?Tool Usage: AskUserQuestions
Use AskUserQuestions when questions have a finite set of likely answers. Use open-ended follow-up when answers are unbounded.
When to Use Structured Options
| Question Pattern | Example | Options Style |
|---|---|---|
| Priority/ranking | "Is this must-have or nice-to-have?" | Single select: Must-have, Should-have, Nice-to-have |
| Format selection | "What export format?" | Multi-select: CSV, JSON, Excel, PDF |
| Scope decisions | "MVP or full version?" | Single select: MVP, Full, Phased |
| Yes/No with nuance | "Auth required?" | Single select: Public, Authenticated, Role-based |
When to Use Open-Ended
- "Describe the user journey in your own words"
- "What problem does this solve?"
- "Walk me through the workflow"
Example: Structured Elicitation
For a "User Export" feature, batch related choices:
Question 1 (header: "Export scope"): "What data should users be able to export?" Options: "Own data only", "Team data", "Organization-wide", multi-select enabled
Question 2 (header: "Format"): "Which export formats should be supported?" Options: "CSV", "JSON", "Excel (.xlsx)", "PDF", multi-select enabled
Question 3 (header: "Priority"): "How critical is this feature?" Options: "Must-have (blocking)", "Should-have (important)", "Nice-to-have (future)"
Interview Flow
Phase 1: Discovery
Use open-ended questions to understand the problem space:
- "Tell me about this feature in your own words"
- "What problem are we solving?"
Then use AskUserQuestions to narrow down:
- Target users (single select from identified personas)
- Usage frequency (Daily, Weekly, Monthly, Rarely)
- Priority (Must-have, Should-have, Nice-to-have)
Phase 2: Details
Use AskUserQuestions for scope and constraint decisions:
- Scope: MVP vs Full vs Phased (single select)
- Key capabilities (multi-select from discovered items)
Then open-ended: "Walk me through the user journey"
Phase 3: Edge Cases
Use AskUserQuestions for technical trade-offs:
- Error handling approach (Retry, Fail fast, Queue, Notify)
- Data limits (multi-select thresholds)
Then open-ended: "What happens when [X] fails?"
Phase 4: Validation
Present spec summary, then use AskUserQuestions:
- "Does this capture your requirements?" (Yes / Needs changes / Major gaps)
- Per-requirement priority confirmation if needed
Multi-Agent Pre-Discovery
For features spanning multiple domains, launch Task subagents with relevant skills before starting the interview. This front-loads technical context so the interview focuses on decisions rather than exploration.
Pattern: Parallel Skill-Invoked Discovery
User request: "I need a feature that does X"
Before interview, launch subagents in parallel:
- Task(subagent_type="general-purpose"): Invoke architecture-designer skill to assess system impact
- Task(subagent_type="general-purpose"): Invoke security-reviewer skill to identify auth/data concerns
- Task(subagent_type="Explore"): Search codebase for existing patterns related to the feature
Collect subagent findings → Use them to inform interview questionsThis ensures the Feature Forge interview starts with concrete technical context rather than assumptions.
Quick Reference
| Phase | Focus | Tool |
|---|---|---|
| Pre-Discovery | Technical context | Task subagents with skills |
| Discovery | Problem, users, value | Open-ended → AskUserQuestions |
| Details | Journey, scope, constraints | AskUserQuestions → Open-ended |
| Edge Cases | Failures, limits, security | AskUserQuestions → Open-ended |
| Validation | Summary, gaps | AskUserQuestions |