First attempt will be 95% garbage: A staff engineer's 6-week journey with Claude Code

In an exploration of integrating AI into software development, the author recounts their journey from writing code manually to leveraging AI tools like Claude Code for 80% of initial implementations, shifting their focus to architecture, review, and managing multiple development threads. The process involves iterative attempts to refine AI-generated code, treating AI as a "junior developer" who requires constant context setting due to its inability to retain learning across sessions. The author highlights the need for creating project-specific context files and integrating AI with tools like Linear and GitHub to optimize workflow. They emphasize a three-step review process involving AI, personal, and team evaluations to maintain code quality and address persistent challenges such as AI's confident generation of faulty code and context limitations in large codebases. The post also discusses the financial and productivity benefits of AI, encouraging tech leads to support engineers in experimenting with AI solutions, particularly for repetitive tasks, while documenting processes to enhance efficiency. The author reflects on the emotional shift from code ownership to problem-solving, suggesting that the future of development lies in the synergy between developers and AI, where developers become orchestrators of AI agents to deliver faster and more efficient solutions.