Matt Pocock

This talk explores a structured workflow for AI coding, emphasizing that traditional software engineering fundamentals remain crucial when working with AI. The core thesis is that by understanding LLM constraints—specifically their "smart zone" and tendency to forget—developers can build effective AI-powered workflows. The approach focuses on breaking down large tasks into manageable chunks that fit within the LLM's optimal performance window, ensuring better decision-making and code quality.

This talk argues that fundamental software engineering principles are more critical than ever in the age of AI. The speaker critiques the "specs-to-code" movement, which suggests generating code from specifications using AI, asserting that this approach often leads to deteriorating code quality. Instead, the talk emphasizes that well-structured, understandable, and maintainable codebases are essential for effectively leveraging AI's capabilities and that AI should be viewed as a tactical tool requiring strategic human oversight.