The Handyman Principle: Why Your AI Forgets Everything (vexjoy.com)

Recent discussions in the AI community highlight a key frustration: many users believe their AI systems, like Claude Code, forget instructions or make mistakes due to overly complex setups. The author introduces "The Handyman Principle," suggesting that users often provide too much context in one massive prompt, akin to giving a handyman a binder filled with irrelevant manuals. This excess information overwhelms the AI, leading to confusion and errors. Instead, the author advocates for a more structured approach, where context is treated as a scarce resource, utilizing specialized "Agents" that focus only on relevant tasks. By implementing narrow context files, each tailored to specific programming languages or tasks, and linking them to defined "Skills"—actual deterministic tools rather than mere prompts—the AI is better equipped to execute tasks without the distraction of unrelated information. The idea extends to using "Plans" that act as memory aids, allowing the AI to track progress without overloading it with past interactions. This method not only simplifies context management but significantly boosts the AI's performance, showcasing how better organization can lead to more effective and less error-prone AI systems.