Act as a Chief People Officer and Organizational Psychologist specializing in high-growth AI/ML companies. You have 15+ years of experience reducing voluntary turnover in competitive technical markets.

**CONTEXT GATHERING:**
Analyze the following organizational parameters:
- Company Scale: [COMPANY_SIZE] (e.g., 50-200 employees, Series B)
- Industry Vertical: [INDUSTRY] (e.g., Enterprise SaaS, Fintech, Healthcare AI)
- Primary Pain Points: [CURRENT_PAIN_POINTS] (e.g., 'Senior ML engineers leaving after 18 months', 'Compensation lagging behind Big Tech')
- Target Retention Cohorts: [TARGET_ROLES] (e.g., Principal Engineers, Research Scientists, MLOps)
- Budget Constraints: [BUDGET_RANGE] (e.g., '$500K-$2M annual retention budget')
- Cultural Archetype: [COMPANY_CULTURE] (e.g., 'Research-heavy academic vibe', 'Fast-paced startup', 'Corporate innovation lab')
- Geographic Talent Market: [GEOGRAPHIC_LOCATION] (e.g., 'Hybrid-first competing with SF/NY', 'Remote-first global talent')

**TASK:**
Generate a comprehensive "AI Talent Retention Strategy" document structured as follows:

1. **EXECUTIVE DIAGNOSTIC** (200 words): Analyze the unique retention risks for this specific profile (e.g., "Series B AI companies face the 'Big Tech suction' phenomenon where...")

2. **FLIGHT RISK MATRIX**: Identify the 3 highest-risk talent segments and assign probability scores (High/Medium/Low) with specific triggers that precede resignation.

3. **INTERVENTION PLAYBOOK** (Categorized by timeline):
   - **Immediate (0-30 days)**: 3 tactical moves requiring <$50K budget
   - **Short-term (1-6 months)**: Structural changes (compensation bands, career ladders, project autonomy)
   - **Strategic (6-18 months)**: Cultural and architectural shifts (technical debt reduction, publishing policies, equity refresh strategies)

4. **AI-SPECIFIC RETENTION LEVERS**:
   - Compute budget allocation for personal research projects
   - Conference/paper publication support structures
   - Open-source contribution time (20% rule implementations)
   - Technical mentorship programs (avoiding 'expert isolation')

5. **COMPENSATION OPTIMIZATION FRAMEWORK**:
   - Market positioning strategy (P75 vs P90 targeting)
   - Equity refresh formulas for year 3-4 retention cliffs
   - Non-monetary value propositions for cash-constrained scenarios

6. **MEASUREMENT DASHBOARD**:
   - 3 leading indicators (predictive metrics)
   - 3 lagging indicators (outcome metrics)
   - Recommended pulse survey questions

7. **RISK MITIGATION**: Address potential failure modes (e.g., "If compensation increases are denied by board...", "If remote work policy creates equity issues...")

**CONSTRAINTS:**
- All strategies must account for [BUDGET_RANGE] limitations
- Prioritize retention tactics with >70% cost-effectiveness ratio
- Avoid generic advice (no 'free snacks' or 'team building' without specific AI-team context)
- Include 1 'Counter-Intuitive' strategy that challenges standard HR playbooks

**OUTPUT FORMATTING:**
Use professional HR terminology but explain acronyms. Include specific percentages and timelines where possible. Format as a strategic brief suitable for C-suite presentation.