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.
Sourcegraph searches code. CodeSee maps architecture. Glue discovers what your codebase actually does — features, health, ownership — and why that matters more.
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 ask the wrong questions about AI coding tools. Here are the 8 questions that actually matter—and why context is the real problem.
Most developers waste 30-90 minutes understanding code context before writing a single line. Here's how to optimize your AI coding workflow.
Claude and Copilot fail on real codebases because they lack context. Here's why AI coding tools break down—and what actually works for complex engineering tasks.
Enterprise orchestration platforms promise unified workflows but ignore the code underneath. Here's why context matters more than coordination.
AI coding tools promise 10x productivity but deliver 10x confusion instead. The problem isn't the AI—it's the missing context layer your team ignored.
Forget feature lists. This guide ranks AI coding assistants by what matters: context quality, codebase understanding, and real-world developer experience.
AI coding assistants promise magic but deliver mediocrity without context. Here's what vendors won't tell you about hallucinations, costs, and the real solution.
Model Context Protocol connects AI tools to real data. Here's everything you need to know about MCP servers, security, and practical implementation.
Bolt.new is great for prototypes, but enterprise teams need more. Here are the alternatives that actually handle production codebases at scale.
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.
Most AI code reviewers catch formatting issues. Here's what tools actually find logic bugs, race conditions, and security holes—and why context matters.
CTOs ask the hard questions about AI coding tools. We answer them with real security implications, implementation strategies, and context architecture.
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.
AI coding tools generate code fast but lack context. Here's what actually works in 2026 and why context-aware platforms change everything.
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.
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.
Stop building AI features that hallucinate in production. Context engineering is the difference between demos that wow and systems that ship.
AI code generation isn't optional anymore. Here's what CTOs ask about GitHub Copilot, Cursor, and why context matters more than the model.
AI coding assistants hallucinate solutions that don't fit your codebase. Here's how to actually debug with AI that understands your architecture.
Stop using ChatGPT as a search engine. MCP lets AI assistants access your feature catalog, code health data, and competitive gaps directly.
Low-code platforms promise speed but deliver technical debt nobody talks about. Here's what the $65B market boom means for engineering teams.
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.
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.
AI coding tools ship features fast but leave you vulnerable. Here's how to test code you barely understand — and why context matters more than coverage.
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.
AI code completion breaks down on cross-file refactors, legacy code, and tickets requiring business context. The problem isn't the AI — it's the context gap.
Engineering teams lose 20-35% of developer time to context acquisition. This invisible tax is baked into every estimate and accepted as normal. It shouldn't be.
Why 60+ specialized MCP tools beat generic LLM prompting for code intelligence. Deep dive into the protocol that makes AI actually useful for developers.
How AI-powered codebase context and code tours transform developer onboarding from months of tribal knowledge transfer to weeks of guided exploration.
A buyer's guide to code intelligence platforms. What to look for, what to ignore, and how to run a meaningful proof of concept.
Claude Code is powerful but limited by what it can see. Here's how to feed it codebase-level context for dramatically better results on complex tasks.
Comprehensive comparison of the top AI coding tools — Copilot, Cursor, Claude Code, Cody, and more. Updated for 2026 with real benchmarks on complex codebases.
A practical guide to combining Glue's codebase intelligence with Cursor's AI editing for a workflow that understands before it generates.
Code search finds where code is. Code intelligence tells you why it exists, what depends on it, and what breaks if you change it.
Side-by-side comparison of Lovable and Dev for AI-powered application building. When to use each and how they compare to code intelligence tools.
An honest comparison of code intelligence tools. What each does best, where each falls short, and how to choose.