bi-agents/.agents/skills/bmad-brainstorming/steps/step-02b-ai-recommended.md

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:

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

Append to document:

## 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!