AI agent development shifts toward loop engineering and automated workflows

The field of AI development is shifting from manual prompt engineering toward “loop engineering,” a method that transforms one-shot prompts into repeatable, automated processes. This approach utilizes loops, teams, and harnesses to manage AI agents more effectively.

Moadim has introduced an open-source loop engine designed to run AI agents—such as Claude, Codex, Hermes, or Pi—on a schedule or specific trigger. The engine functions as a portable in-process scheduler that dispatches loops within isolated workbenches, eliminating the need for a host cron daemon. It provides integrated interfaces including REST, MCP, and a web UI.

Broader industry trends indicate that AI agents are increasingly being organized into squads and fleets to divide responsibilities like planning, implementation, and testing. Furthermore, the concept of “harnesses” is becoming critical, providing the necessary tools, permissions, memory, and orchestration to control a model’s environment and capabilities.