Large language models are increasingly extensible. Whether they’re called “skills,” “plugins,” “tools,” or “MCP servers,” the core idea is the same: let an LLM invoke external code, read external data, and act on external instructions. It’s also one of the most serious attack surfaces in modern AI systems. Table Of Contents What’s the problem? Prompt […]
Read More →If you take one thing from Claude Code, make it this: Explore → Plan → Code → Commit. The developers who skip straight to “write me the code,” then spend the next hour arguing with the output. This workflow exists to prevent that. Explore Before writing a single line, Claude needs context. Without it, you get […]
Read More →Forward Deployed Engineer (FDE) is the most in-demand technical role in AI right now. Not because of the title, because of the problem it solves. AI research labs are shipping capabilities faster than enterprises can absorb them. The gap between what is technically possible and what is actually running in production is enormous, and closing […]
Read More →A practical guide for developers navigating Claude Code, Cursor, Copilot, Windsurf, Codex, and beyond. You switch from Cursor to Claude Code. Or from Copilot to Windsurf. The interface is different. The shortcuts are different. The config file has a new name. And for a moment, it feels like you’re starting from scratch. You’re not. Under […]
Read More →The rise of AI coding assistants—Cursor, Claude, GitHub Copilot—has shifted the main challenge from writing code to communicating intent. When engineers give an LLM a vague feature description or unstructured prompt, the model often drifts. It invents edge cases, guesses API endpoints, or generates lots of valid code that solves the wrong problem. To keep […]
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