Chris Parsons' updated guide emphasizes using AI for coding, focusing on verification and the shift from human review to automated checks. He advocates for "agentic engineering" and highlights the importance of tools like Claude Code and Codex CLI. Verification is prioritized over speed of code generation, focusing on building robust review processes. The core role of the programmer shifts to training AI and shaping the development "harness". The article references Birgitta Böckeler's work on "Harness Engineering," highlighting the benefits of computational sensors. Adam Tornhill's point highlights how function length is related to structuring code and intention. Nilay Patel's points about the "software brain" view of the world provide perspective. The article stresses consistent data definitions, essential for effective AI interactions. The author shares the observation that AI professionals are racing to make themselves "legible" to AI tools. The author explores his personal experience of using AI and his perspective on the impact of AI on work.