Schema Coevolution
The collaborative development process between human and LLM for evolving the configuration layer of llm-wiki-pattern systems. The schema document (CLAUDE.md, AGENTS.md, etc.) grows and adapts based on actual usage patterns, domain needs, and discovered workflows.
Core Concept
Unlike static system configurations, the schema in an LLM wiki system evolves with use. As humans and LLMs work together, they discover:
- Effective workflows for the specific domain
- Useful page formats and structures
- Domain-specific conventions and tags
- Optimal ingest and query patterns
These discoveries get documented in the schema, making the LLM a more effective collaborator over time.
Evolution Process
Initial Schema
- Basic structure and conventions
- Generic workflows from the pattern
- Minimal domain-specific customization
Usage-Driven Refinement
- Workflow optimization: Discovering efficient ingest patterns
- Convention standardization: Establishing consistent tagging and formatting
- Domain adaptation: Adding field-specific page types and structures
- Tool integration: Incorporating discovered utilities and scripts
Continuous Improvement
- Regular schema updates based on what works
- Documentation of effective practices
- Removal of unused conventions
- Addition of new capabilities
Human-LLM Collaboration
Human Contributions
- Domain expertise: Understanding field-specific needs
- Workflow preferences: Preferred interaction patterns
- Quality standards: Defining acceptable outputs
- Strategic direction: Long-term knowledge goals
LLM Contributions
- Pattern recognition: Identifying recurring structures
- Consistency maintenance: Ensuring schema adherence
- Workflow execution: Following documented procedures
- Improvement suggestions: Proposing optimizations
Schema Components That Evolve
Page Types
- Standard templates for different content types
- Domain-specific entity categories
- Specialized analysis formats (comparisons, timelines, etc.)
Tagging Systems
- Hierarchical tag structures for the domain
- Consistent naming conventions
- Cross-reference patterns
Workflows
- Detailed ingest procedures
- Query and synthesis patterns
- Maintenance and lint operations
- Quality control checkpoints
Tool Integration
- CLI utilities and their usage patterns
- Search and navigation tools
- Export and visualization formats
- Integration with external systems
Benefits
Adaptive Systems
Schema coevolution enables knowledge systems that improve with use rather than becoming stale or rigid.
Domain Optimization
Over time, the system becomes specifically tuned to the user's field and preferences rather than remaining generic.
Reduced Friction
Well-evolved schemas reduce cognitive overhead by codifying effective practices and eliminating decision fatigue.
Knowledge Transfer
The schema serves as documentation of effective knowledge management practices that can be shared or adapted.
Example Evolution
Initial: "Create entity pages for people mentioned"
Evolved: "Create entity pages with standardized sections: Background, Key Ideas, Publications, Influence, Cross-References. Tag with domain (ai-researcher, entrepreneur, academic) and confidence level."
Challenges
Over-Specification
Schemas can become too rigid, constraining useful variation and experimentation.
Version Management
Managing schema changes while maintaining consistency across existing wiki content.
Complexity Growth
Balancing comprehensive documentation with usability for both human and LLM.
Implementation Patterns
Versioned Schemas
Track schema evolution with version control to understand what changes improve effectiveness.
Modular Structure
Organize schema into sections (workflows, conventions, formats) that can evolve independently.
Example-Driven Documentation
Include concrete examples in schema documentation to clarify abstract conventions.
See also
- llm-wiki-pattern - System using schema coevolution
- three-layer-architecture - Schema as configuration layer
- adaptive-systems - Systems that improve with use
- workflow-optimization - Process improvement patterns