Proof capsule
Knowledge / Data Contracts
Reliability architecture for AI/knowledge pipelines
A contract architecture for making AI and knowledge pipelines inspectable, testable, and maintainable.
Problem
LLM and knowledge workflows often grow as brittle chains of scripts, folders, exports, and hidden assumptions. As soon as more repos, agents, documents, summaries, or publishers interact, the system becomes hard to debug and unsafe to extend.
What I built
A public manual and contract catalog that defines buses, integration seams, run records, manifests, observability indexes, snapshot publishing, and contract tests for a multi-repo knowledge ecosystem.
What this proves
- Design reliability layers that keep multi-repo AI/data pipelines inspectable and safe to extend.
- Define boundaries, contracts, observability, versioning, integration governance, and failure containment.
- Turn knowledge-system architecture into explicit rules rather than hidden coupling between folders and scripts.
Key principles
- Consumers read contracts and indexes, not private directories.
- Every pipeline run emits an audit record.
- Cross-repo integration is artifact-based, not code-coupled.
- UI surfaces read compact indexes, not raw stores.
- Contract tests define whether a project is integrated.