GlueDevSecOps Evolution FAQ: AI-Powered Security for Modern Development
DevSecOps is shifting from rule-based scanning to AI-powered analysis. Here's what actually works when securing modern codebases at scale.
DevSecOps FAQ: AI for Software Development Security
Security tools scan for known vulnerabilities but miss architectural flaws. AI needs codebase context to understand real attack surfaces and data flows.
AI for Software Development FAQ: The Shift-Everywhere Approach
Shift-left is dead. Modern AI requires code intelligence at every stage. Here's what actually works when AI needs to understand your entire codebase.
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.
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.
AI Code Review Tools That Actually Find Bugs, Not Just Style Issues
Most AI code reviewers catch formatting issues. Here's what tools actually find logic bugs, race conditions, and security holes—and why context matters.
Building a Blast Radius Oracle: How I Designed Impact Analysis
I built Glue's blast radius analysis by mapping files to features, dependencies, and impact zones. Here's why most change analysis tools fail.
AI-Ready Legacy Transformation: Modernize Systems for Context
Legacy systems are black boxes to AI coding tools. Here's how to make decades-old code readable to both humans and LLMs without a full rewrite.
AI for Software Development: Beyond Shift-Left to Shift-Everywhere
Shift-left is dead. Modern AI doesn't just catch bugs earlier—it understands your entire codebase at every stage. Here's what shift-everywhere actually means.
AI for Product Managers: 8 Essential FAQs That Reveal the Future
Most PMs ask the wrong questions about AI. Here are 8 that actually matter — and how code intelligence gives you answers marketing can't fake.
Future of AI for Product Managers: Essential Strategies for 2025
AI won't replace PMs. But PMs who understand their codebase through AI will replace those who don't. Here's what actually matters in 2025.
Context-Aware Development Tools: The Mistake Killing 73% of Team Productivity
Your team's AI coding tools generate garbage because they're context-blind. Here's why 73% of AI code gets rejected and how context awareness fixes it.
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.
Why Your Codebase Is a Graph, Not Files
Deep dive into graph-based code analysis and why traditional file-based thinking fails at scale.
Competitive Intelligence from Code: How Gap Analysis Works
Automated competitive gap detection that scans competitor features and maps them against your codebase. Real intelligence, not guesswork.
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.
Neuromorphic Computing FAQ: 8 Critical Questions About Brain-Inspired AI
Neuromorphic chips process data like the brain. What this means for AI applications, when it matters, and what developers need to know.