We’ve all seen the demos: an AI builds a flashy app from scratch, and everyone asks, "What prompt did you use?" But try that "magic prompt" on a massive legacy system or deep inside Linux OS tools, and it falls apart. The "perfect prompt" is a myth. In real-world codebases, agents suffer from "Context Amnesia" - forgetting architectural constraints as the chat grows. They also over-engineer, duplicate code, hallucinate and add redundant fallbacks just to be safe.

This is why human engineers are irreplaceable. We hold the big-picture context and the judgment of what not to build.

This talk cuts through the "autonomous AI" hype. Instead of endless prompt-hacking, I’ll share a practical, design-first workflow for tools like Cursor and Claude Code. You will learn how to:

• Anchor Context: use Markdown design docs as the agent's "external memory."
• Filter the Bloat: force agents to plan first, catching garbage before it's coded.
• Steer, Don't Prompt: recover when the agent gets stuck.