interview-conducting
AI-led stakeholder interviews using LLMREI research-backed patterns. Conducts structured interviews to elicit requirements through context-adaptive questioning, active listening, and systematic requirement extraction.
What this skill does
# Interview Conducting Skill
AI-led stakeholder interviews using research-backed LLMREI patterns for effective requirements elicitation.
## When to Use This Skill
**Keywords:** stakeholder interview, requirements interview, LLMREI, elicit requirements, talk to stakeholder, interview session, user interview, customer interview
Invoke this skill when:
- Conducting a structured requirements interview with a stakeholder
- Exploring user needs through conversation
- Gathering requirements from subject matter experts
- Clarifying and deepening understanding of requirements
## Interview Modes
### Real Stakeholder Interview
When interviewing an actual person through the chat interface:
```yaml
mode: real_stakeholder
approach:
- Use AskUserQuestion tool for structured questions
- Allow natural conversation flow
- Adapt questions based on responses
- Summarize and confirm understanding periodically
```
### Simulated Interview (Solo Mode)
When no real stakeholder is available:
```yaml
mode: simulated
approach:
- Spawn persona agent via Task tool
- Conduct interview with simulated stakeholder
- Mark requirements with lower confidence
- Flag items needing real stakeholder validation
```
## Interview Structure (LLMREI Pattern)
### Phase 1: Opening (2-3 minutes)
**Goals:**
- Establish rapport
- Set expectations
- Explain the process
**Questions:**
- "Thank you for your time. Could you briefly describe your role and how you interact with this project?"
- "What outcomes would make this interview successful for you?"
### Phase 2: Context Gathering (5-10 minutes)
**Goals:**
- Understand stakeholder perspective
- Identify key concerns
- Map relationships
**Question Types:**
- Role-based: "How does your team currently handle X?"
- Priority-based: "What are your top three concerns about this project?"
- Relationship-based: "Who else should we talk to about X?"
### Phase 3: Requirements Exploration (15-25 minutes)
**Goals:**
- Elicit functional requirements
- Identify non-functional requirements
- Uncover constraints and assumptions
**Question Pathways:**
```text
Start with open-ended → Follow up with specifics → Validate understanding
Example:
Q1: "What should the system do when a user logs in?"
Q2: "You mentioned 'quick access to dashboard' - what does quick mean to you?"
Q3: "So the login should complete in under 2 seconds and show the dashboard. Is that right?"
```
### Phase 4: Validation (5-10 minutes)
**Goals:**
- Summarize key requirements
- Verify understanding
- Identify gaps
**Techniques:**
- Read back requirements for confirmation
- Ask "What have we missed?"
- Prioritize using MoSCoW
### Phase 5: Closing (2-3 minutes)
**Goals:**
- Thank stakeholder
- Explain next steps
- Offer follow-up
## Question Types
### Context-Independent Questions
General questions applicable to any interview:
| Question | Purpose |
|----------|---------|
| "What is your primary goal for this system?" | High-level vision |
| "Who are the main users?" | User identification |
| "What existing systems does this replace/integrate with?" | Context mapping |
| "What would failure look like?" | Risk identification |
### Context-Deepening Questions
Follow up on stakeholder responses to get specifics:
```text
Pattern: [Stakeholder says X] → "When you say X, what specifically do you mean?"
Examples:
- "fast" → "What response time are you expecting? Under 1 second?"
- "secure" → "What specific security requirements apply? Authentication methods?"
- "easy to use" → "Can you describe what easy means? Any specific workflows?"
```
### Context-Enhancing Questions
Introduce considerations the stakeholder may not have mentioned:
```text
Pattern: Suggest possibilities based on domain knowledge
Examples:
- "Have you considered how this works on mobile devices?"
- "What happens if the user loses connectivity mid-operation?"
- "How should the system handle peak load during [known busy period]?"
```
## Requirement Extraction
As requirements emerge, capture them in this format:
```yaml
requirement:
id: REQ-{number}
text: "{requirement statement}"
source: interview
stakeholder: "{role}"
timestamp: "{ISO-8601}"
type: functional|non-functional|constraint
priority: must|should|could|wont
confidence: high|medium|low
raw_quote: "{exact stakeholder words if notable}"
```
## Common Mistakes to Avoid
| Mistake | Prevention |
|---------|------------|
| Very long questions | Keep questions concise and focused |
| Multiple unrelated questions | One question at a time |
| Leading questions | Use neutral language |
| Skipping NFRs | Explicitly ask about performance, security, usability |
| No summary | Recap periodically to verify understanding |
| Rushing | Allow silence; stakeholders often add important details |
## Interview Summary Template
After each interview, generate:
```yaml
interview_summary:
session_id: "INT-{number}"
stakeholder_role: "{role}"
duration_minutes: {number}
date: "{ISO-8601}"
autonomy_level: "{guided|semi-auto|full-auto}"
key_themes:
- "{theme-1}"
- "{theme-2}"
requirements_elicited:
- id: REQ-{number}
text: "{requirement}"
confidence: high|medium|low
type: functional|non-functional|constraint
priority: must|should|could
follow_up_needed:
- "{question or topic needing clarification}"
stakeholder_quotes:
- "{notable direct quote}"
observations:
- "{interviewer observation about needs or concerns}"
next_steps:
- "{recommended action}"
```
## Delegation
For specific techniques, delegate to:
- **LLMREI patterns**: Load `references/llmrei-patterns.md` from parent skill
- **Stakeholder simulation**: Invoke `stakeholder-simulation` skill
- **Domain research**: Invoke `domain-research` skill for background
## Output Location
Save interview results to:
```text
.requirements/{domain}/interviews/INT-{number}.yaml
```
## Related
- `elicitation-methodology` - Parent hub skill
- `stakeholder-simulation` - For simulated interviews
- `gap-analysis` - Post-interview completeness checking
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