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Building the future of AI-assisted development. Real engineering, real decisions.
LLM context windows are finite. When AI loses context about your codebase, it generates code that breaks architecture, ignores existing patterns, and introduces subtle bugs. These articles document how we're solving that with GraphRAG — building a knowledge graph of your codebase so AI can query what it needs, instead of guessing. Real decisions, real tradeoffs, written as we build.
What is Context Engineering for AI-Assisted Development?
Context engineering is the practice of structuring knowledge so AI systems can reason about code before generating it. Learn how it differs from prompt engineering and why it matters for production software.
Read article → TechnicalGraphRAG for Code: How Knowledge Graphs Fix AI Code Generation
Traditional RAG fails for code because it treats source files as flat documents. GraphRAG builds a knowledge graph of your codebase — functions, classes, dependencies — so AI can reason about architecture.
Read article →Stop re-explaining your codebase to AI
Cerebro builds a knowledge graph of your project so AI understands architecture before generating a single line. BYOK — use your own API key.
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