Codebase understanding is the most important developer skill nobody teaches. Schools teach algorithms. Bootcamps teach frameworks. Nobody teaches: “here’s a 500K-line codebase you’ve never seen — figure out how to make a safe change.”
This guide covers every technique and tool for understanding codebases, from basic to AI-powered.
Level 1: Manual Techniques
grep / ripgrep
The oldest tool. Search for text patterns across files. Fast and reliable for known terms. Useless for understanding structure or relationships.
IDE Navigation
Jump to definition, find references, peek at implementations. Essential for tracing individual call paths. Doesn’t scale to understanding features or system-level behavior.
git blame / git log
See who wrote code and when. Read PR descriptions for context. The most underused understanding technique — git history contains enormous amounts of context that developers rarely access.
Reading Code
Sometimes you just have to read it. Start at the entry point, trace the flow, build a mental model. This works for small areas but doesn’t scale to large codebases.
Level 2: Search and Navigation Tools
Sourcegraph
Cross-repository code search. Find any symbol, pattern, or reference across your entire codebase. The best tool for “where is this?” questions.
IDE Extensions
CodeLens, bracket colorizers, call hierarchy views. Improve the in-editor experience for tracing and understanding.
Level 3: AI-Powered Understanding
Code Intelligence Platforms (Glue)
Full codebase analysis: feature discovery, dependency graphs, knowledge extraction, blast radius analysis. Answers “why” and “what if” questions, not just “where.”
AI Chat with Context (Claude Code + MCP)
Natural language questions about your codebase with traced answers. “How does authentication work?” returns a specific, accurate walkthrough — not a generic description.
Auto-Generated Documentation
Feature catalogs, API docs, and architecture overviews generated from code analysis. Always current because they’re derived from the code, not written separately.
Choosing Your Approach
- Solo developer, small codebase: Manual techniques + IDE navigation
- Small team, growing codebase: Add Sourcegraph for search
- Mid-size team, complex codebase: Add code intelligence (Glue) for understanding
- Large team, enterprise codebase: Full stack — search, intelligence, AI chat, automated documentation
The investment in understanding tools should match the Understanding Tax. If your team spends 20-30% of time on context acquisition, the ROI on intelligence tools is immediate.
Originally published on glue.tools. Glue is the pre-code intelligence platform — paste a ticket, get a battle plan.