Honest answers to common questions about AI coding tools. Learn how context-aware platforms solve problems that ChatGPT and Copilot can't touch.
Enterprise orchestration platforms promise unified workflows but ignore the code underneath. Here's why context matters more than coordination.
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.
After 6 months with both tools, I learned the real productivity gain isn't the AI—it's the context you give it. Here's what actually matters.
AI applications demand different API patterns. Here's how to design endpoints that handle streaming, context windows, and unpredictable load without breaking.
AI coding tools generate code fast but lack context. Here's what actually works in 2026 and why context-aware platforms change everything.
CTOs ask the hard questions about low-code platforms. Here's what nobody tells you about the $65B industry—from vendor lock-in to the mess it leaves behind.
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.
Raw code metrics lie to you. Stop drowning in file-level data. Learn how context intelligence platforms turn code into features, ownership, and strategy.
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.