BMAD-METHOD/bmad-agent/consultation/multi-persona-protocols.md

Multi-Persona Consultation Protocols (Memory-Enhanced)

Purpose

Enable structured consultation between multiple BMAD personas simultaneously while maintaining clear role boundaries and leveraging accumulated consultation intelligence for superior collaborative problem-solving.

Memory-Enhanced Consultation Types

Design Review Council

Participants: PM + Architect + Design Architect Memory Context: Previous design decisions, successful architecture patterns, UI/UX outcome patterns Use Cases:

• Major architectural decisions with UI implications
• Technology choices affecting user experience
• Design system and component architecture decisions
• Performance vs. aesthetics trade-offs

Memory-Enhanced Protocol:

1. Pre-Consultation Memory Briefing: Search for similar design decisions and their outcomes
2. PM Problem Presentation: Enhanced with memory of similar product requirements and their design implications
3. Independent Analysis Phase: Each specialist provides analysis informed by relevant memory patterns
4. Memory-Informed Debate: Structured discussion leveraging lessons from similar past decisions
5. Consensus Building: Decision-making enhanced with memory of successful design decision outcomes
6. Memory Documentation: Capture consultation outcome with rich context for future reference

Technical Feasibility Panel

Participants: Architect + Dev + SM Memory Context: Implementation complexity patterns, timeline estimation accuracy, technical risk outcomes Use Cases:

• Implementation complexity assessment for new features
• Timeline estimation and resource planning
• Technical risk evaluation and mitigation planning
• Technology evaluation and adoption decisions

Memory-Enhanced Protocol:

1. Context Loading: Search memory for similar technical assessments and their accuracy
2. Architect Technical Requirements: Present requirements enhanced with memory of similar technical challenges
3. Dev Implementation Analysis: Complexity assessment informed by memory of similar implementation outcomes
4. SM Project Impact Evaluation: Timeline and resource analysis enhanced with memory of similar project patterns
5. Collaborative Risk Assessment: Combined analysis leveraging memory of technical risk outcomes
6. Memory-Informed Estimation: Provide estimates enhanced with memory of similar project completion patterns

Product Strategy Committee

Participants: PM + PO + Analyst Memory Context: Market strategy outcomes, feature prioritization results, scope decision impacts Use Cases:

• Market strategy and positioning decisions
• Feature prioritization and roadmap planning
• Scope decisions and MVP definition
• User feedback integration and product direction

Memory-Enhanced Protocol:

1. Market Intelligence Integration: Analyst presents research enhanced with memory of similar market contexts
2. Product Strategy Analysis: PM provides strategy perspective informed by memory of similar product outcomes
3. Development Impact Assessment: PO evaluates current development impact using memory of similar scope changes
4. Strategic Alignment Discussion: Collaborative analysis leveraging memory of successful product strategies
5. Prioritized Recommendations: Decision-making enhanced with memory of feature prioritization outcomes

Emergency Response Team

Participants: Context-dependent (2-3 most relevant personas) Memory Context: Crisis resolution patterns, rapid decision outcomes, emergency response effectiveness Use Cases:

• Critical bugs requiring immediate resolution
• Scope emergencies and major requirement changes
• Technical blockers threatening project timeline
• Resource or timeline crisis management

Memory-Enhanced Rapid Response Protocol:

1. Immediate Memory Query: Search for similar crisis situations and resolution patterns (1 minute)
2. Rapid Problem Assessment: 5 minutes per persona enhanced with memory of similar crisis patterns
3. Memory-Informed Options: Identify action options based on memory of successful crisis resolutions
4. Risk/Benefit Analysis: Quick analysis leveraging memory of similar decision outcomes
5. Rapid Decision with Learning: Make decision enhanced with memory insights and document for future crises

Memory-Enhanced Consultation Structure Template

Opening Phase (5 minutes) - Memory-Informed Setup

Moderator Role: PO or user-designated Memory Integration: Search for similar consultation contexts and successful facilitation patterns

1. Problem Statement with Context: Clear issue description enhanced with relevant memory context
2. Historical Context Briefing: Brief presentation of similar past situations and their outcomes
3. Consultation Objectives: Decision goals informed by memory of successful consultation outcomes
4. Constraints with Precedent: Limitations enhanced with memory of how similar constraints were handled
5. Success Criteria: Measures informed by memory of effective consultation outcomes

Analysis Phase (15 minutes) - Memory-Enhanced Individual Perspectives

Individual Perspectives (5 minutes each persona): Memory Enhancement: Each persona briefed with relevant domain-specific memories before analysis

Per-Persona Memory Briefing Template:

## 🎭 {Persona Name} - Memory-Enhanced Consultation Brief

### Your Domain Context
**Current Situation**: {immediate_consultation_context}
**Your Expertise Focus**: {persona_domain_responsibility}

### 📚 Relevant Memory Context
**Similar Situations You've Handled**:
- **Case 1**: {similar_situation_summary} → **Outcome**: {result} → **Lesson**: {key_insight}
- **Case 2**: {similar_situation_summary} → **Outcome**: {result} → **Lesson**: {key_insight}

**Successful Patterns in Your Domain**:
- ✅ **What typically works**: {proven_approaches_for_persona}
- ⚠️ **Common pitfalls to avoid**: {anti_patterns_for_persona}
- 🎯 **Best practices**: {optimization_patterns_for_persona}

### 🤝 Cross-Persona Collaboration Insights
**Effective Collaboration Patterns**: {memory_of_successful_consultation_approaches}
**Communication Strategies**: {proven_ways_to_convey_domain_expertise}
**Common Integration Points**: {typical_overlap_areas_with_other_personas}

### 💡 Consultation-Specific Intelligence
**For This Type of Decision**: {consultation_type_specific_insights}
**Typical Outcomes**: {memory_of_similar_consultation_results}
**Success Factors**: {what_typically_leads_to_good_outcomes}

Synthesis Phase (10 minutes) - Memory-Enhanced Collaborative Analysis

Collaborative Discussion Structure:

1. Agreement Identification with Precedent: Where personas align, enhanced with memory of similar consensus outcomes
2. Disagreement Mapping with Historical Context: Specific contentions analyzed against memory of similar debates and their resolutions
3. Trade-off Analysis with Outcome Memory: Pros/cons discussion leveraging memory of similar trade-off outcomes
4. Assumption Validation with Pattern Recognition: Challenge assumptions using memory of similar assumption failures/successes

Resolution Phase (10 minutes) - Memory-Enhanced Decision Making

Decision Making Process:

1. Consensus Check with Confidence Scoring: Agreement assessment enhanced with memory-based confidence levels
2. Minority Opinion Documentation: Dissenting views captured with memory context of similar minority positions and their eventual validation
3. Implementation Considerations with Pattern Application: Next steps informed by memory of similar decision implementation outcomes
4. Success Monitoring Plan: Tracking approach based on memory of effective decision outcome measurement

Memory-Enhanced Quality Control Measures

Role Integrity Maintenance with Memory Support

• Memory-Informed Persona Consistency: Each persona maintains perspective enhanced with domain-specific memory context
• Historical Pattern Validation: Ensure persona advice aligns with memory of their successful domain approaches
• Cross-Consultation Learning: Apply memory of effective persona collaboration patterns
• Expertise Boundary Enforcement: Use memory patterns to maintain clear domain expertise boundaries

Structured Communication with Memory Intelligence

• Memory-Informed Facilitation: Moderator uses memory of successful consultation facilitation patterns
• Historical Context Integration: Relevant past consultation outcomes woven into discussion
• Pattern Recognition Facilitation: Moderator identifies emerging patterns based on memory of similar consultations
• Learning Integration: Real-time application of consultation improvement insights from memory

Decision Documentation with Memory Enhancement

Enhanced Consultation Record:

# Memory-Enhanced Multi-Persona Consultation Summary
**Date**: {timestamp}
**Type**: {consultation-type}  
**Participants**: {persona-list}
**Duration**: {actual-time}

## Problem Context
**Current Issue**: {problem-description}
**Historical Context**: {similar-past-situations}
**Memory Insights Applied**: {relevant-historical-lessons}

## Individual Perspectives (Memory-Enhanced)
### {Persona 1 Name}
**Analysis**: {domain-specific-perspective}
**Memory Context Applied**: {relevant-historical-patterns}
**Confidence Level**: {confidence-based-on-similar-situations}

[Similar structure for each participant]

## Consensus Decision
**Final Recommendation**: {decision}
**Memory-Informed Rationale**: {reasoning-enhanced-with-historical-context}
**Implementation Approach**: {next-steps-based-on-proven-patterns}
**Success Probability**: {confidence-based-on-similar-outcomes}%

## Historical Validation
**Similar Past Decisions**: {relevant-precedents}
**Outcome Patterns**: {what-typically-happens-with-similar-decisions}
**Risk Mitigation**: {preventive-measures-based-on-memory}

## Learning Integration
**New Patterns Identified**: {novel-insights-from-this-consultation}
**Refinements to Existing Patterns**: {updates-to-memory-based-on-outcomes}
**Cross-Consultation Insights**: {collaboration-improvements-discovered}

## Memory Creation
**Memories Created**: 
- Decision Memory: {decision-memory-summary}
- Consultation Pattern Memory: {collaboration-pattern-memory}
- Outcome Tracking Memory: {success-monitoring-memory}

Consultation Effectiveness Enhancement

Pre-Consultation Optimization

Memory-Based Participant Selection:

• Analyze problem type against memory of most effective persona combinations
• Select participants based on memory of successful collaboration patterns
• Consider consultation type effectiveness history for optimal duration and structure

During-Consultation Intelligence

Real-Time Memory Integration:

• Surface relevant memories as consultation topics emerge
• Provide historical context for emerging disagreements
• Apply memory of successful conflict resolution patterns
• Use memory of effective decision-making approaches

Post-Consultation Learning

Consultation Outcome Tracking:

def track_consultation_outcome(consultation_id, implementation_details):
    outcome_memory = {
        "type": "consultation_outcome",
        "consultation_id": consultation_id,
        "implementation_approach": implementation_details,
        "participants": consultation_participants,
        "decision": final_decision,
        "success_metrics": define_success_criteria(),
        "follow_up_schedule": [
            {"timeframe": "1_week", "check": "immediate_implementation_issues"},
            {"timeframe": "1_month", "check": "decision_effectiveness"},
            {"timeframe": "3_months", "check": "long_term_outcome_validation"}
        ],
        "collaboration_effectiveness": rate_collaboration_quality(),
        "memory_insights_effectiveness": rate_memory_integration_value()
    }
    
    add_memories(outcome_memory, tags=["consultation", "outcome", consultation_type])

Integration with BMAD Orchestrator

Consultation Mode Activation

## Consultation Commands Integration
- `/consult {type}`: Activate memory-enhanced consultation with automatic participant selection
- `/consult custom {persona1,persona2,persona3}`: Custom consultation with memory briefing for selected personas
- `/consult-history`: Show memory of past consultations and their outcomes
- `/consult-patterns`: Display successful consultation patterns for current context

Memory-Enhanced Consultation Flow

1. Command Recognition: Orchestrator identifies consultation request
2. Memory Context Loading: Search for relevant consultation patterns and outcomes
3. Participant Briefing: Each selected persona receives memory-enhanced domain briefing
4. Structured Facilitation: Execute consultation protocol with memory integration
5. Outcome Documentation: Create rich memory entries for future consultation enhancement
6. Learning Integration: Update consultation effectiveness patterns based on outcomes

Quality Assurance Integration

• Consultation Effectiveness Tracking: Monitor success rates of memory-enhanced consultations vs. standard approaches
• Pattern Refinement: Continuously improve consultation protocols based on outcome memory
• Participant Optimization: Learn optimal persona combinations for different problem types
• Facilitation Enhancement: Improve moderation approaches based on consultation outcome patterns