bzzz/SLURP_CONTEXTUAL_INTELLIGENCE_PLAN.md

BZZZ Leader-Coordinated Contextual Intelligence System

Implementation Plan with Agent Team Assignments

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Executive Summary

Implement a sophisticated contextual intelligence system within BZZZ where the elected Leader node acts as Project Manager, generating role-specific encrypted context for AI agents. This system provides the "WHY" behind every UCXL address while maintaining strict need-to-know security boundaries.

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System Architecture

Core Principles

1. Leader-Only Context Generation: Only the elected BZZZ Leader (Project Manager role) generates contextual intelligence
2. Role-Based Encryption: Context is encrypted per AI agent role with need-to-know access
3. Bounded Hierarchical Context: CSS-like cascading context inheritance with configurable depth limits
4. Decision-Hop Temporal Analysis: Track related decisions by decision distance, not chronological time
5. Project-Aligned Intelligence: Context generation considers project goals and team dynamics

Key Components

• Leader Election & Coordination: Extend existing BZZZ leader election for Project Manager duties
• Role-Based Context Engine: Sophisticated context extraction with role-awareness
• Encrypted Context Distribution: Need-to-know context delivery through DHT
• Decision Temporal Graph: Track decision influence and genealogy
• Project Goal Alignment: Context generation aligned with mission objectives

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Agent Team Assignment Strategy

Core Architecture Team

• Senior Software Architect: Overall system design, API contracts, technology decisions
• Systems Engineer: Leader election infrastructure, system integration, performance optimization
• Security Expert: Role-based encryption, access control, threat modeling
• Database Engineer: Context storage schema, temporal graph indexing, query optimization

Implementation Team

• Backend API Developer: Context distribution APIs, role-based access endpoints
• DevOps Engineer: DHT integration, monitoring, deployment automation
• Secrets Sentinel: Encrypt sensitive contextual information, manage role-based keys

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Detailed Implementation with Agent Assignments

Phase 1: Leader Context Management Infrastructure (2-3 weeks)

1.1 Extend BZZZ Leader Election

Primary Agent: Systems Engineer
Supporting Agent: Senior Software Architect
Location: pkg/election/

Systems Engineer Tasks:

• Configure leader election process to include Project Manager responsibilities
• Implement context generation as Leader-only capability
• Set up context generation failover on Leader change
• Create Leader context state synchronization infrastructure

Senior Software Architect Tasks:

• Design overall architecture for leader-based context coordination
• Define API contracts between Leader and context consumers
• Establish architectural patterns for context state management

1.2 Role Definition System

Primary Agent: Security Expert
Supporting Agent: Backend API Developer
Location: pkg/roles/

Security Expert Tasks:

• Extend existing agent/role_config.go for context access patterns
• Define security boundaries for role-based context requirements
• Create role-to-encryption-key mapping system
• Implement role validation and authorization mechanisms

Backend API Developer Tasks:

• Implement role management APIs
• Create role-based context access endpoints
• Build role validation middleware

1.3 Context Generation Engine

Primary Agent: Senior Software Architect
Supporting Agent: Backend API Developer
Location: slurp/context-intelligence/

Senior Software Architect Tasks:

• Design bounded hierarchical context analyzer architecture
• Define project-goal-aware context extraction patterns
• Architect decision influence graph construction system
• Create role-relevance scoring algorithm framework

Backend API Developer Tasks:

• Implement context generation APIs
• Build context extraction service interfaces
• Create context scoring and relevance engines

Phase 2: Encrypted Context Storage & Distribution (2-3 weeks)

2.1 Role-Based Encryption System

Primary Agent: Security Expert
Supporting Agent: Secrets Sentinel
Location: pkg/crypto/

Security Expert Tasks:

• Extend existing Shamir's Secret Sharing for role-based keys
• Design per-role encryption/decryption architecture
• Implement key rotation mechanisms
• Create context compartmentalization boundaries

Secrets Sentinel Tasks:

• Encrypt sensitive contextual information per role
• Manage role-based encryption keys
• Monitor for context information leakage
• Implement automated key revocation for compromised roles

2.2 Context Distribution Network

Primary Agent: DevOps Engineer
Supporting Agent: Systems Engineer
Location: pkg/distribution/

DevOps Engineer Tasks:

• Configure efficient context propagation through DHT
• Set up monitoring and alerting for context distribution
• Implement automated context sync processes
• Optimize bandwidth usage for context delivery

Systems Engineer Tasks:

• Implement role-filtered context delivery infrastructure
• Create context update notification systems
• Optimize network performance for context distribution

2.3 Context Storage Architecture

Primary Agent: Database Engineer
Supporting Agent: Backend API Developer
Location: slurp/storage/

Database Engineer Tasks:

• Design encrypted context database schema
• Implement context inheritance resolution queries
• Create decision-hop indexing for temporal analysis
• Design context versioning and evolution tracking

Backend API Developer Tasks:

• Build context storage APIs
• Implement context retrieval and caching services
• Create context update and synchronization endpoints

Phase 3: Intelligent Context Analysis (3-4 weeks)

3.1 Contextual Intelligence Engine

Primary Agent: Senior Software Architect
Supporting Agent: Backend API Developer
Location: slurp/intelligence/

Senior Software Architect Tasks:

• Design file purpose analysis with project awareness algorithms
• Architect architectural decision extraction system
• Design cross-component relationship mapping
• Create role-specific insight generation framework

Backend API Developer Tasks:

• Implement intelligent context analysis services
• Build project-goal alignment APIs
• Create context insight generation endpoints

3.2 Decision Temporal Graph

Primary Agent: Database Engineer
Supporting Agent: Senior Software Architect
Location: slurp/temporal/

Database Engineer Tasks:

• Implement decision influence tracking (not time-based)
• Create context evolution through decisions schema
• Build "hops away" similarity scoring queries
• Design decision genealogy construction database

Senior Software Architect Tasks:

• Design temporal graph architecture for decision tracking
• Define decision influence algorithms
• Create decision relationship modeling patterns

3.3 Project Goal Alignment

Primary Agent: Senior Software Architect
Supporting Agent: Systems Engineer
Location: slurp/alignment/

Senior Software Architect Tasks:

• Design project mission context integration architecture
• Create team goal awareness in context generation
• Implement strategic objective mapping to file purposes
• Build context relevance scoring per project phase

Systems Engineer Tasks:

• Integrate goal alignment with system performance monitoring
• Implement alignment metrics and reporting
• Optimize goal-based context processing

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Security & Access Control

Role-Based Context Access Matrix

Role	Context Access	Encryption Level	Scope
Senior Architect	Architecture decisions, system design, technical debt	High	System-wide
Frontend Developer	UI/UX decisions, component relationships, user flows	Medium	Frontend scope
Backend Developer	API design, data flow, service architecture	Medium	Backend scope
DevOps Engineer	Deployment config, infrastructure decisions	High	Infrastructure
Project Manager (Leader)	All context for coordination	Highest	Global

Encryption Strategy

• Multi-layer encryption: Base context + role-specific overlays
• Key derivation: From role definitions and Shamir shares
• Access logging: Audit trail of context access per agent
• Context compartmentalization: Prevent cross-role information leakage

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Integration Points

Existing BZZZ Systems

• Leverage existing DHT for context distribution
• Extend current election system for Project Manager duties
• Integrate with existing crypto infrastructure
• Use established UCXL address parsing

External Integrations

• RAG system for enhanced context analysis
• Git repository analysis for decision tracking
• CI/CD pipeline integration for deployment context
• Issue tracker integration for decision rationale

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Success Criteria

1. Context Intelligence: Every UCXL address has rich, role-appropriate contextual understanding
2. Security: Agents can only access context relevant to their role
3. Efficiency: Context inheritance eliminates redundant storage (target: 85%+ space savings)
4. Decision Tracking: Clear genealogy of how decisions influence other decisions
5. Project Alignment: Context generation reflects current project goals and team structure

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Implementation Timeline

• Phase 1: Leader infrastructure (2-3 weeks)
• Phase 2: Encryption & distribution (2-3 weeks)
• Phase 3: Intelligence engine (3-4 weeks)
• Integration & Testing: (1-2 weeks)

Total Timeline: 8-12 weeks

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Next Steps

1. Senior Software Architect: Review overall system architecture and create detailed technical specifications
2. Security Expert: Design role-based encryption scheme and access control matrix
3. Systems Engineer: Plan Leader election extensions and infrastructure requirements
4. Database Engineer: Design context storage schema and temporal graph structure
5. DevOps Engineer: Plan DHT integration and monitoring strategy
6. Backend API Developer: Design API contracts for context services
7. Secrets Sentinel: Design role-based encryption key management

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Architecture Decisions

Why Leader-Only Context Generation?

• Consistency: Single source of truth for contextual understanding
• Quality Control: Prevents conflicting or low-quality context from multiple sources
• Security: Centralized control over sensitive context generation
• Performance: Reduces computational overhead across the network

Why Role-Based Encryption?

• Need-to-Know Security: Each agent gets exactly the context they need
• Compartmentalization: Prevents context leakage across role boundaries
• Scalability: New roles can be added without affecting existing security
• Compliance: Supports audit requirements and access control policies

Why Decision-Hop Analysis?

• Conceptual Relevance: Like RAG, finds related decisions by influence, not time
• Project Memory: Preserves institutional knowledge about decision rationale
• Impact Analysis: Shows how changes propagate through the system
• Learning: Helps AI agents understand decision precedents and patterns

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This plan represents the foundation for creating an intelligent, secure, contextual memory system for the entire AI development team, with the BZZZ Leader acting as the coordinating Project Manager who ensures each team member has the contextual understanding they need to excel in their role.