GlueGlue.tools vs Competition: Complete 2025 Product Intelligence Comparison
Sourcegraph searches code. CodeSee maps architecture. Glue discovers what your codebase actually does — features, health, ownership — and why that matters more.
From Whiteboard to Code Graphs: Building an AI Context Layer
Architecture diagrams are lies the moment you draw them. Here's how to build living code graphs that actually reflect your system—and why AI needs them.
Code Graphs FAQ: Framework-Aware AI Context Layer Guide
Code graphs power modern dev tools, but most are syntax trees in disguise. Here's what framework-aware graphs actually do and why they matter for AI context.
Blast Radius Oracle FAQ: Building Code Change Impact Analysis
How we built a system that predicts what breaks when you change code. File-to-feature mapping, call graphs, and risk scoring that actually works.
Knowledge Graphs for Codebases: The Future of Developer Tools
Why representing your codebase as a knowledge graph changes everything — from AI assistance to onboarding. The data model matters more than the tools.
How Top Engineering Teams Use Dependency Graphs to Ship Faster
Dependency graphs aren't just debugging tools. Smart teams use them to parallelize work, prevent merge conflicts, and cut release cycles by weeks.
Building AI Coding Agents That Actually Understand Your Codebase
AI coding agents fail because they lack context. Here's how to give them the feature maps, call graphs, and ownership data they need to work.
Building a Blast Radius Oracle: How We Designed Impact-of-Change Analysis
Most impact analysis tools are wrong. We built a system that combines static analysis, runtime traces, and LLM reasoning to actually predict what breaks.
The Ultimate Guide to Enterprise AI Context Management
AI coding assistants fail at scale because they lack context. Here's how to build a context graph that makes AI actually useful in enterprise codebases.
How We Cluster 4,000 Files Into Features Using Louvain Community Detection
Technical deep dive into graph-based feature discovery. How Louvain modularity optimization groups files into meaningful features automatically.
Your Codebase Knows Everything Your Team Has Forgotten
Git history, call graphs, and change patterns contain more reliable tribal knowledge than any wiki. The problem isn't capturing knowledge — it's extracting it.
Call Graphs That Prevent Production Incidents
How understanding code dependencies and blast radius before deployment prevents the bugs that code review misses.
Why Your Codebase Is a Graph, Not Files
Deep dive into graph-based code analysis and why traditional file-based thinking fails at scale.
How to Evaluate Code Intelligence Tools in 2026
A buyer's guide to code intelligence platforms. What to look for, what to ignore, and how to run a meaningful proof of concept.
Why Sourcegraph Isn't Enough: Code Search vs Code Intelligence
Code search finds where code is. Code intelligence tells you why it exists, what depends on it, and what breaks if you change it.
Embedding vs Knowledge Graphs for Code Intelligence
Vector embeddings find similar code. Knowledge graphs find connected code. Why the best systems use both.
Glue vs CodeSee vs Sourcegraph: Code Intelligence Compared
An honest comparison of code intelligence tools. What each does best, where each falls short, and how to choose.
Stop Hand-Rolling Feature Discovery: Here Is the Math That Actually Works
Manual feature mapping is expensive, incomplete, and always stale. Graph-based automated discovery finds features humans miss. Here is the algorithm.