Framework | Notion

🎯 A comprehensive approach to failure management in Symphony's extension ecosystem

🔍 Problem Statement

Symphony's extension-based architecture requires a robust failure handling system that:

⚖️ Balances autonomy with reliability across community-developed extensions
📊 Learns from real-world failures rather than theoretical predictions
🛡️ Enforces consistent standards while allowing extension flexibility
🎼 Enables intelligent orchestration by the Conductor model

📊 Realistic Failure Probability Assessment

🎯 Base Failure Rate Assumptions

Since we cannot predict real-world failure rates, Symphony uses evidence-based baseline assumptions:

Extension Type	Base Failure Rate	Rationale
🧩 Motifs (UI Components)	0%	Static UI components rarely fail during execution
⚙️ Operators (Utility Functions)	1%	Simple logic with predictable inputs/outputs
🎻 Instruments (AI Models)	5%	Complex AI operations with external dependencies

📈 Dynamic Learning System

Initial Rate (Baseline) → Real Usage → Recorded Failures → Updated Probability
       ↓                      ↓              ↓                    ↓
    5% (AI Model) → 100 uses → 8 failures → 8% actual rate

Key Benefits:

🎯 Realistic baselines set appropriate expectations
📊 Continuous learning improves accuracy over time
🔄 Self-correcting system based on actual performance
🎨 Per-extension tracking allows fine-grained reliability assessment