Library
Books & Guides
Free resources on code intelligence, semantic search, and AI-assisted development. No sign-up required.
The Code Intelligence Buyer's Guide
How to Evaluate AI Code Search for Your Team
The costs your team is already paying for bad context, what code intelligence actually is, and a decision framework for build vs. buy vs. embed. Includes security, compliance, and economics analysis.
Rolling Out AI Code Search
Adoption, Measurement, and the 90-Day Plan
The implementation playbook: champion-pilot-rollout framework, KPIs that matter, monorepo considerations, CI/CD integration, and a week-by-week 90-day plan.
Code Search Patterns
50 Query Recipes for Debugging, Reviews, Onboarding, and Architecture
A cookbook of 50 semantic search recipes organized by task: debugging, code review, onboarding, refactoring, architecture, performance, and security.
The Vibe Coder's Survival Guide
How to Ship, Debug, and Grow When AI Writes Your Code
For developers who learned to code with AI. Covers reading unfamiliar code, mental models, spotting AI mistakes, debugging without panic, testing, and building real expertise.
Vibe Coding, Real Debugging
A Developer's Guide to Debugging What AI Built
The debugging mindset shift for AI-assisted development. Covers context systems, semantic search for debugging, graph-based impact analysis, and building a complete debugging workflow.
Local-First AI
Code Intelligence Without the Cloud Dependency
Where your code goes when you use AI tools, the compliance landscape (HIPAA, SOC 2, FedRAMP, ITAR), local-first architecture, hybrid architectures, and a 28-item buyer's checklist.
Code Retrieval from Scratch
Chunking, Embeddings, and Hybrid Search for Code
Build a code retrieval system from zero. Covers chunking strategies, embedding models, BM25, hybrid retrieval with Reciprocal Rank Fusion, and AST graph boosting. Includes runnable Python code.
Production Code Search
Reranking, Scaling, and Evaluating Code Retrieval Systems
Take code search from prototype to production. Cross-encoder reranking, adaptive thresholds, cold start optimization, incremental indexing at scale, and evaluation with MRR/nDCG.