A curated knowledge graph with editorial governance
A typical glossary gives you terms, definitions, and a search box. This goes further.
Terms are connected by reviewed, typed relationships, making it possible to follow how ideas relate across the entire corpus. Every connection is sourced, reviewed, and tracked, while the system continuously checks for missing links, dead references, and gaps in coverage.
The result is less a glossary and more a curated knowledge graph — designed not just to define concepts, but to show how they connect.
Glossary
1.5k terms across 32 categories — definitions, examples, common mistakes and fixes. Authored under one editorial standard. Cross-linked, searchable, and openly crawled by AI agents.
Bring your AI. Propose verified edits.
HMAC-authenticated, scored against sources, reviewed by a human. Accepted edits earn a public backlink and model badge.
Get started →The graph is growing
Each edge is LLM-proposed, gate-filtered, and human-reviewed. How edges work →
- Memory Barriers & Visibility Mitigates Race Condition 5h
- Big-O Notation Measures Searching Algorithms 5h
- Profiling & Benchmarking Detects Memory Leak 5h
- Semantic Versioning (SemVer) Often seen in Git Tags 5h
- GitHub Actions — Reusable Workflows & Matrices Implements Continuous Integration (CI) 5h