Phase 1: Retrieval & Knowledge Systems · 30 hours · Python (ingestion) · TypeScript (API + UI)

Capstone 02 — RAG over Codebase (Cross-Repo Semantic Search)

Every serious engineering org in 2026 runs an internal code search that understands meaning, not just strings.

Hiring signal: Can build capstone 02 end to end

Introduction

Sourcegraph Amp, Cursor's codebase answers, Augment's enterprise graph, Aider's repomap, Pinterest's internal MCP — same shape. Ingest many repos, parse with tree-sitter, embed function- and class-level chunks, hybrid-search, re-rank, answer with citations. This capstone asks you to build one that handles 2M lines of code across 10 repos and survives incremental re-indexing on every git push.

Phases exercised: P5 · P7 · P11 · P13 · P17

Type: Capstone Languages: Python (ingestion), TypeScript (API + UI) Prerequisites: Phase 5 (NLP foundations), Phase 7 (transformers), Phase 11 (LLM engineering), Phase 13 (tools), Phase 17 (infrastructure) Time: 30 hours

Objective

Learning objectives

Unlock the full lesson

You've read the first 2 sections. The rest of this lesson covers The Problem, The Concept, Build, Check Yourself, Key Terms & Next — plus a hands-on lab, quiz, and project artifact.

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