The author reflects on imposter syndrome as a software engineer in the age of AI coding tools. While LLMs and agentic harnesses have crossed the "can it be done" threshold, they lack true reasoning and struggle with software architecture, maintainability, and clean interfaces. The craft of building debuggable, composable software still requires human expertise in managing abstractions and cognitive load. Despite AI's capabilities in following instructions and tool calling, fundamental limitations like prompt injection vulnerabilities remain. The author emphasizes that good software engineering is about thoughtful choices, tradeoffs, and understanding how components work together over time.