## Memory System Enhancements
- **Individual agent memory integration**: Every agent response now triggers automatic memory pattern extraction through on_agent_response() hooks
- **Enhanced conversation logging**: Added detailed message breakdown showing USER/ASSISTANT/TOOL message counts and tool names called
- **Fixed infrastructure extraction**: Resolved hardcoded agent name issues by using SREConstants for agent identification
- **Comprehensive memory persistence**: All agent responses and tool executions stored as conversation memory with proper session tracking
## Tool Architecture Clarification
- **Centralized memory access**: Confirmed only supervisor agent has direct access to memory tools (retrieve_memory, save_*)
- **Individual agent focus**: Individual agents have NO memory tools, only domain-specific tools (5 tools each for metrics, logs, k8s, runbooks)
- **Automatic pattern recognition**: Memory capture happens automatically through hooks, not manual tool calls by individual agents
## Documentation Updates
- **Updated memory-system.md**: Comprehensive design documentation reflecting current implementation
- **Added example analyses**: Created flight-booking-analysis.md and api-response-time-analysis.md in docs/examples/
- **Enhanced README.md**: Added memory system overview and personalized investigation examples
- **Updated .gitignore**: Now ignores entire reports/ folder instead of just .md files
## Implementation Improvements
- **Event ID tracking**: All memory operations generate and log event IDs for verification
- **Pattern extraction confirmation**: Logs confirm pattern extraction working for all agent types
- **Memory save verification**: Comprehensive logging shows successful saves across all memory types
- **Script enhancements**: manage_memories.py now handles duplicate removal and improved user management
Infrastructure Memory Parsing Improvements:
- Fix infrastructure memory parsing to handle both JSON and plain text formats
- Convert plain text memories to structured InfrastructureKnowledge objects
- Change warning logs to debug level for normal text-to-structure conversion
- Ensure all infrastructure memories are now retrievable and usable
User Personalization Documentation:
- Add comprehensive memory system analysis comparing Alice vs Carol reports
- Create docs/examples/ folder with real investigation reports demonstrating personalization
- Document side-by-side communication differences based on user preferences
- Show how same technical incident produces different reports for different user roles
Example Reports Added:
- Alice's technical detailed investigation report (technical role preferences)
- Carol's business-focused executive summary report (executive role preferences)
- Memory system analysis with extensive side-by-side comparisons
This demonstrates the memory system's ability to:
- Maintain technical accuracy while adapting presentation style
- Apply user-specific escalation procedures and communication channels
- Build institutional knowledge about recurring infrastructure patterns
- Personalize identical technical incidents for different organizational roles
