Graph engineering for AI agents: the 9-stage knowledge-graph pipeline (translated from SEU's graduate course) + task-graph orchestration patterns, as a Claude skill with teaching mode and paste-ready workflows
A Survey on Ontology Engineering, Graph Engineering, Loop Engineering, Harness Engineering, Context Engineering and Prompt Engineering
An end to end implementation of Graph Engineering as proposed by Andrew NG and Peter Steinberger
An open-source graph engineering runtime that keeps orchestration in TypeScript and delegates semantic work to replaceable Agent runtimes.
Graph Engineering, simplified β with GraphCode. #graphcode
Deterministic memory layer for your agents
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AI skill for typed, auditable workflow graphs, conditional routing, evidence-gated evolution, and validation. Includes full source, examples, and tests.
Personal-memory-driven AI work twin that uses Codex to work inside real projects.