Mission Impossible: Taming AI Agents in the Wild

This article tackles the challenges and strategies for effectively controlling AI agents in various fields, especially software development. The author shares hard-won lessons emphasizing meticulous planning and constraining the context of what AI agents can do. It delves into choosing tools, planning tasks, creating and revising plans, testing those plans, and identifying larger architectural problems. Key aspects like rules, performance payback, model selection, and cost control are also covered. The author details their experience using tools like Cursor to create reusable plans, iteratively refining and testing them for improved reliability, ultimately leading to efficient software development.