AI is not replacing software engineers wholesale — it's automating routine, execution-level coding tasks. The shift demands developers move from effort-based to impact-based engineering: understanding system architecture, applying clean code principles, debugging complex distributed systems, and taking ownership of outcomes. A five-step roadmap is outlined: strengthen CS fundamentals, build real-world systems with failure handling, master debugging, use AI as a tool rather than a crutch, and establish proof of work through public building and open-source contributions. The core argument is that source code is now a byproduct of thinking, not the primary output.