Moadim Launches Open-Source Loop Engine to Automate AI Agent Workflows
The Rust-based daemon enables 'loop engineering' by scheduling recurring AI agent routines in isolated local environments.
Moadim.io has launched an open-source loop engine and scheduler designed to transition AI interaction from manual prompting to automated, recurring routines. The system allows developers to deploy AI agents on a fixed schedule to autonomously manage repositories and complex tasks.
Built as a local Rust-based daemon, Moadim enables users to define "loops"—specific combinations of a prompt, a schedule, and a chosen AI agent. These loops execute automatically within isolated workbenches using tmux, ensuring agent processes remain separated. To maintain system stability, the engine includes a built-in watchdog to identify and kill hung runs. The software is released under the MIT license and supports macOS and Linux via launchd and systemd. Notably, Moadim utilizes a portable in-process scheduler, meaning it does not require a host cron daemon to function.
The Shift to Loop Engineering
The project arrives during a broader industry shift toward "loop engineering." While traditional prompt engineering focuses on the quality of a single interaction, loop engineering places agents into recurring cycles. This approach allows AI to move beyond one-off responses to perform continuous maintenance on codebases or persistent monitoring of data streams. By structuring agentic workflows into cycles, developers can create autonomous systems that evolve and react to changes in a project without constant human intervention.
Infrastructure and Compatibility
To ensure flexibility, Moadim is agent-agnostic, supporting a variety of models including Claude, Codex, Hermes, NanoClaw, and Pi. For those using the built-in Claude agent, the system requires python3 on the PATH to pre-seed MCP-approval state and unattended trust. Management of these routines is handled through three simultaneous interfaces: a Web UI, a REST API featuring Swagger/OpenAPI documentation, and the Model Context Protocol (MCP).
Industry Implications
By providing a local-first infrastructure for orchestration, Moadim offers a standardized alternative to proprietary cloud schedulers. This architecture is critical for developers prioritizing data privacy and system-level control, as it keeps the orchestration layer on the user's own hardware. The integration of MCP further allows these automated loops to interact with a wider ecosystem of tools and data sources, reducing the friction of building complex, multi-model AI pipelines.
Future Outlook
As the concept of loop engineering matures, the focus will likely shift toward how these recurring agents coordinate with one another. While Moadim provides the scheduling and isolation layer, the efficiency of these loops remains dependent on the underlying models' ability to handle long-term state and recurring tasks without degradation.