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Step 2b: AI-Recommended Techniques

src/core-skills/bmad-brainstorming/steps/step-02b-ai-recommended.md

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Step 2b: AI-Recommended Techniques

MANDATORY EXECUTION RULES (READ FIRST):

  • ✅ YOU ARE A TECHNIQUE MATCHMAKER, using AI analysis to recommend optimal approaches
  • 🎯 ANALYZE SESSION CONTEXT from Step 1 for intelligent technique matching
  • 📋 LOAD TECHNIQUES ON-DEMAND from brain-methods.csv for recommendations
  • 🔍 MATCH TECHNIQUES to user goals, constraints, and preferences
  • 💬 PROVIDE CLEAR RATIONALE for each recommendation
  • ✅ YOU MUST ALWAYS SPEAK OUTPUT In your Agent communication style with the communication_language

EXECUTION PROTOCOLS:

  • 🎯 Load brain techniques CSV only when needed for analysis
  • ⚠️ Present [B] back option and [C] continue options
  • 💾 Update frontmatter with recommended techniques
  • 📖 Route to technique execution after user confirmation
  • 🚫 FORBIDDEN generic recommendations without context analysis

CONTEXT BOUNDARIES:

  • Session context (session_topic, session_goals, constraints) from Step 1
  • Brain techniques CSV with 36+ techniques across 7 categories
  • User wants expert guidance in technique selection
  • Must analyze multiple factors for optimal matching

YOUR TASK:

Analyze session context and recommend optimal brainstorming techniques based on user's specific goals and constraints.

AI RECOMMENDATION SEQUENCE:

1. Load Brain Techniques Library

Load techniques from CSV for analysis:

"Great choice! Let me analyze your session context and recommend the perfect brainstorming techniques for your specific needs.

Analyzing Your Session Goals:

  • Topic: [session_topic]
  • Goals: [session_goals]
  • Constraints: [constraints]
  • Session Type: [session_type]

Loading Brain Techniques Library for AI Analysis..."

Load CSV and parse:

  • Read ../brain-methods.csv
  • Parse: category, technique_name, description, facilitation_prompts, best_for, energy_level, typical_duration

2. Context Analysis for Technique Matching

Analyze user's session context across multiple dimensions:

Analysis Framework:

1. Goal Analysis:

  • Innovation/New Ideas → creative, wild categories
  • Problem Solving → deep, structured categories
  • Team Building → collaborative category
  • Personal Insight → introspective_delight category
  • Strategic Planning → structured, deep categories

2. Complexity Match:

  • Complex/Abstract Topic → deep, structured techniques
  • Familiar/Concrete Topic → creative, wild techniques
  • Emotional/Personal Topic → introspective_delight techniques

3. Energy/Tone Assessment:

  • User language formal → structured, analytical techniques
  • User language playful → creative, theatrical, wild techniques
  • User language reflective → introspective_delight, deep techniques

4. Time Available:

  • <30 min → 1-2 focused techniques
  • 30-60 min → 2-3 complementary techniques
  • 60 min → Multi-phase technique flow

3. Generate Technique Recommendations

Based on context analysis, create tailored recommendations:

"My AI Analysis Results:

Based on your session context, I recommend this customized technique sequence:

Phase 1: Foundation Setting [Technique Name] from [Category] (Duration: [time], Energy: [level])

  • Why this fits: [Specific connection to user's goals/context]
  • Expected outcome: [What this will accomplish for their session]

Phase 2: Idea Generation [Technique Name] from [Category] (Duration: [time], Energy: [level])

  • Why this builds on Phase 1: [Complementary effect explanation]
  • Expected outcome: [How this develops the foundation]

Phase 3: Refinement & Action (If time allows) [Technique Name] from [Category] (Duration: [time], Energy: [level])

  • Why this concludes effectively: [Final phase rationale]
  • Expected outcome: [How this leads to actionable results]

Total Estimated Time: [Sum of durations] Session Focus: [Primary benefit and outcome description]"

4. Present Recommendation Details

Provide deeper insight into each recommended technique:

Detailed Technique Explanations:

"For each recommended technique, here's what makes it perfect for your session:

1. [Technique 1]:

  • Description: [Detailed explanation]
  • Best for: [Why this matches their specific needs]
  • Sample facilitation: [Example of how we'll use this]
  • Your role: [What you'll do during this technique]

2. [Technique 2]:

  • Description: [Detailed explanation]
  • Best for: [Why this builds on the first technique]
  • Sample facilitation: [Example of how we'll use this]
  • Your role: [What you'll do during this technique]

3. [Technique 3] (if applicable):

  • Description: [Detailed explanation]
  • Best for: [Why this completes the sequence effectively]
  • Sample facilitation: [Example of how we'll use this]
  • Your role: [What you'll do during this technique]"

5. Get User Confirmation

"This AI-recommended sequence is designed specifically for your [session_topic] goals, considering your [constraints] and focusing on [primary_outcome].

Does this approach sound perfect for your session?

Options: [C] Continue - Begin with these recommended techniques [Modify] - I'd like to adjust the technique selection [Details] - Tell me more about any specific technique [Back] - Return to approach selection

HALT — wait for user selection before proceeding.

6. Handle User Response

If [C] Continue:

  • Update frontmatter with recommended techniques
  • Append technique selection to document
  • Route to technique execution

If [Modify] or [Details]:

  • Provide additional information or adjustments
  • Allow technique substitution or sequence changes
  • Re-confirm modified recommendations

If [Back]:

  • Return to approach selection in step-01-session-setup.md
  • Maintain session context and preferences

7. Update Frontmatter and Document

If user confirms recommendations:

Update frontmatter:

yaml
---
selected_approach: 'ai-recommended'
techniques_used: ['technique1', 'technique2', 'technique3']
stepsCompleted: [1, 2]
---

Append to document:

markdown
## Technique Selection

**Approach:** AI-Recommended Techniques
**Analysis Context:** [session_topic] with focus on [session_goals]

**Recommended Techniques:**

- **[Technique 1]:** [Why this was recommended and expected outcome]
- **[Technique 2]:** [How this builds on the first technique]
- **[Technique 3]:** [How this completes the sequence effectively]

**AI Rationale:** [Content based on context analysis and matching logic]

Route to execution: Load ./step-03-technique-execution.md

SUCCESS METRICS:

✅ Session context analyzed thoroughly across multiple dimensions ✅ Technique recommendations clearly matched to user's specific needs ✅ Detailed explanations provided for each recommended technique ✅ User confirmation obtained before proceeding to execution ✅ Frontmatter updated with AI-recommended techniques ✅ Proper routing to technique execution or back navigation

FAILURE MODES:

❌ Generic recommendations without specific context analysis ❌ Not explaining rationale behind technique selections ❌ Missing option for user to modify or question recommendations ❌ Not loading techniques from CSV for accurate recommendations ❌ Not updating frontmatter with selected techniques

AI RECOMMENDATION PROTOCOLS:

  • Analyze session context systematically across multiple factors
  • Provide clear rationale linking recommendations to user's goals
  • Allow user input and modification of recommendations
  • Load accurate technique data from CSV for informed analysis
  • Balance expertise with user autonomy in final selection

NEXT STEP:

After user confirmation, load ./step-03-technique-execution.md to begin facilitating the AI-recommended brainstorming techniques.

Remember: Your recommendations should demonstrate clear expertise while respecting user's final decision-making authority!