GlueFrom 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.
Serverless Computing Revolution: How FaaS Became Every Developer's Secret Weapon
Serverless isn't about removing servers—it's about removing server problems. Learn why FaaS won, where it fails, and how to tame distributed complexity.
MCP FAQ: Turn AI Assistants Into Product Intelligence Partners
MCP connects AI assistants to your codebase intelligence. Stop explaining your product architecture—let Claude and Cursor query it directly.
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.
MCP FAQ: Essential Model Context Protocol Questions Answered
Model Context Protocol connects AI tools to real data. Here's everything you need to know about MCP servers, security, and practical implementation.
Enterprise AI Implementation: From Pilot to Production at Scale
Most enterprise AI pilots never reach production. The real blocker isn't the AI—it's understanding your own codebase well enough to integrate it safely.
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.
Understanding and Visualizing Code Architecture for Better Development
Architecture diagrams lie. Learn why static diagrams fail, how to visualize code architecture that stays current, and tools that generate views from actual code.
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.
Best AI Coding Assistants FAQ: Expert Security & Implementation Guide
CTOs ask the hard questions about AI coding tools. We answer them with real security implications, implementation strategies, and context architecture.
API Design for AI-First Applications: Patterns That Scale
AI applications demand different API patterns. Here's how to design endpoints that handle streaming, context windows, and unpredictable load without breaking.
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.
Cloud-Native Development FAQ: Serverless vs Kubernetes Guide
Serverless or Kubernetes? This guide cuts through the hype with real tradeoffs, cost breakdowns, and when each actually makes sense for your team.
Complete Guide to AI SDKs: From Code to Product Success
Most engineers pick an AI SDK and pray it works. Here's how to choose, integrate, and ship AI features without destroying your existing codebase.
Debugging with AI Assistance: Beyond Stack Overflow Copy-Paste
AI coding assistants hallucinate solutions that don't fit your codebase. Here's how to actually debug with AI that understands your architecture.
MCP: The USB-C for AI Apps That Killed Our Glue Code Hell
Model Context Protocol lets AI tools talk to your code, databases, and docs without building custom integrations. Here's why it matters more than the LLM.
Serverless vs Kubernetes: The Cloud-Native Battle Reshaping Tech in 2026
Serverless promises no ops. K8s promises control. Neither delivers what you think. Here's what actually matters when choosing your cloud infrastructure.
Sprint Planning Without 3-Hour Meetings
AI-generated dev plans with file-level tasks based on actual codebase architecture. How to cut sprint planning overhead by 50%.
How to Protect Company Data When Using AI Agents: Complete Guide
Complete guide to securing company data when adopting AI coding agents. Data classification, access controls, audit trails, and practical security architecture.
How to Use AI for Code Review Without Losing the Human Element
AI can flag dependency issues and style violations. Humans should focus on architecture, business logic, and mentoring. Here's how to split the work.
Embedding vs Knowledge Graphs for Code Intelligence
Vector embeddings find similar code. Knowledge graphs find connected code. Why the best systems use both.
Building Scalable AI Applications: Architecture Patterns That Actually Work
Practical architecture patterns for AI-powered applications — from RAG pipelines to agent orchestration. Lessons from building production AI systems.