AI can write user stories in seconds, but most are disconnected from your codebase. Here's how to generate stories that match your actual code capabilities.
Honest answers to common questions about AI coding tools. Learn how context-aware platforms solve problems that ChatGPT and Copilot can't touch.
AI coding tools promise to boost productivity, but most teams struggle with context and code quality. Here's how to actually integrate AI into your workflow.
AI assistants write code fast. Your codebase becomes a mess faster. Here's how to maintain control when AI is writing half your code.
Sourcegraph searches code. CodeSee maps architecture. Glue discovers what your codebase actually does — features, health, ownership — and why that matters more.
I gave AI agents proper context for 30 days. The results: 40% faster onboarding, 60% fewer bugs, and tools that actually understand our codebase.
Your legacy code has no docs? Write PRDs backwards from the implementation. Here's how to extract product specs from code that everyone forgot about.
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.
MCP connects AI assistants to your codebase intelligence. Stop explaining your product architecture—let Claude and Cursor query it directly.
Most developers waste 30-90 minutes understanding code context before writing a single line. Here's how to optimize your AI coding workflow.
Enterprise orchestration platforms promise unified workflows but ignore the code underneath. Here's why context matters more than coordination.
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.
Real answers to hard questions about making AI coding tools actually work. From context windows to team adoption, here's what nobody tells you.
Traditional kanban boards track tickets. AI kanban boards track code, dependencies, and blast radius. Here's why your team needs the upgrade.
The tools you need to ship faster in 2025. From IDE to production, here's what works—and what most teams are missing between code and planning.
You have the perfect requirements template. You still ship the wrong thing. The problem isn't your process—it's that you don't understand your own codebase.
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.
I asked Copilot to fix a bug. It broke 3 features instead. The problem isn't AI—it's that your tools don't know what your code actually does.
A practical guide to combining Glue's codebase intelligence with Cursor's AI editing for a workflow that understands before it generates.
Wikis are always stale. Auto-generated feature catalogs from code analysis are always current. Here's the difference.
AI can flag dependency issues and style violations. Humans should focus on architecture, business logic, and mentoring. Here's how to split the work.
Everything you need to know about codebase understanding tools, techniques, and workflows. From grep to AI-powered intelligence.
AI-native development isn't about using more AI tools. It's about restructuring workflows around AI strengths and human judgment.