Backend Developers
~65 pages
The Developer's Guide to Semantic Code Search
Embeddings, Chunking, and Retrieval - A practical guide to building semantic code search that works at the L1 level
Free Guide
Markdown
By Kelly Price
About This Guide
This guide covers the infrastructure, tradeoffs, and implementation patterns for building semantic code search that actually works at the L1 level — queries where the vocabulary doesn't match the code. Includes embedding model selection, chunking strategies (fixed vs. AST-aware), vector store deployment, query processing, and production hardening with complete Python examples.
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