# Step 6: Risk Assessment

<step-meta>
number: 6
name: risk-assessment
gate: true
</step-meta>

## Mandatory Execution Rules

- READ the complete step file before taking any action
- IDENTIFY risks specific to AI agent implementation
- ALWAYS treat this as collaborative discovery between architectural peers
- FOCUS on risks that could cause implementation divergence

## Execution Protocols

- Show your analysis before taking any action
- Present A/P/C menu after generating risk assessment
- ONLY save when user chooses [C] Continue
- Update frontmatter `stepsCompleted: [1, 2, 3, 4, 5, 6]` before loading next step
- FORBIDDEN to load next step until [C] is selected

## Purpose

Identify technical risks, potential failure modes, and mitigation strategies. Include risks specific to AI-assisted implementation.

## Instructions

1. **Identify Technical Risks**:
   - Performance bottlenecks
   - Single points of failure
   - Security vulnerabilities
   - Data consistency challenges
   - Operational complexity

2. **Assess Impact and Likelihood**:
   - What happens if this risk materializes?
   - How likely is it?
   - What's the blast radius?

3. **Define Mitigations**:
   - How can each risk be reduced or eliminated?
   - What monitoring/alerting is needed?
   - What's the fallback plan?

4. **AI Implementation Risks** (BMAD pattern):
   - Where could AI agents misinterpret requirements?
   - What ambiguities could lead to incompatible implementations?
   - How do we detect implementation drift early?

## Actions

- Analyze: Each component for failure modes
- Review: Security considerations
- Plan: Monitoring and alerting strategy
- Identify: AI implementation risk points

## Output

Add to session file:

```markdown
## Risk Assessment

### Technical Risks

| Risk | Impact | Likelihood | Mitigation |
|------|--------|------------|------------|
| [Risk 1] | High/Med/Low | High/Med/Low | [Strategy] |
| [Risk 2] | High/Med/Low | High/Med/Low | [Strategy] |

### Failure Modes

| Component | Failure Mode | Detection | Recovery |
|-----------|--------------|-----------|----------|
| [A] | [How it fails] | [Monitoring] | [Steps] |
| [B] | [How it fails] | [Monitoring] | [Steps] |

### Security Considerations
- [Authentication approach]
- [Authorization model]
- [Data protection measures]

### AI Implementation Risks
> Risks specific to AI-assisted development

| Risk | Could Cause | Prevention |
|------|-------------|------------|
| Ambiguous requirement | Inconsistent implementation | [Clarification needed] |
| Missing constraint | Invalid assumptions | [Explicit documentation] |

### Operational Readiness
- Monitoring: [What to watch]
- Alerting: [Thresholds]
- Runbooks: [Key procedures needed]
```

<!-- GATE -->

## Collaboration Menu (A/P/C)

After generating risk assessment, present choices:

- **[A] Advanced Elicitation** - Use discovery protocols to explore hidden risks or unconsidered failure modes
- **[P] Party Mode** - Bring multiple perspectives to identify risks from different operational angles
- **[C] Continue** - Save the content and proceed to documentation
- **[R] Revise** - Need to address unacceptable risks before proceeding

## Advanced Elicitation Mode

When user selects [A]:
1. Explore cascading failure scenarios
2. Question security assumptions
3. Investigate edge cases in error handling
4. Challenge operational readiness

## Party Mode

When user selects [P]:
1. Present risk assessment from multiple viewpoints:
   - **Security auditor**: What attack vectors exist?
   - **Site reliability engineer**: What will page us at 3am?
   - **Compliance officer**: What regulatory risks exist?
   - **Incident responder**: How will we debug failures?
2. Synthesize perspectives into comprehensive risk register

## Success Metrics

- Technical risks identified with impact assessment
- Failure modes documented with recovery procedures
- Security considerations explicitly addressed
- AI implementation risks identified and mitigated
- User confirmed risks are acceptable before proceeding

## Failure Modes

- Overlooking critical failure scenarios
- Underestimating risk impact or likelihood
- Missing security considerations
- Not addressing AI implementation risks
- Proceeding without user confirmation
