AI Agent Task Manager

What is AI Agent Task Manager?

AI Agent Task Manager is a browser-based tool that allows users to run multiple autonomous AI coding agents simultaneously. It provides a visual workboard where each column represents a separate agent session, and tasks can be queued with detailed instructions. The system automates task pulling, execution, and reporting, notifying users only when human input is genuinely needed.

Who is it for?

It is designed for developers, teams, and project managers who manage multiple AI coding agents or automate complex workflows. It benefits those working on parallel feature development, bug fixes, refactoring, or backlog processing, enabling efficient oversight of autonomous agents without constant terminal monitoring.

How is it priced?

The tool is free to use with no signup required. Connecting agents and syncing across devices requires signing in with Google, but the core functionality is available at no cost. Additional features like notifications may involve free or paid components, but the main system is free.

How does it compare to alternatives?

This product is a specialized task management system tailored for running multiple autonomous AI coding agents in parallel. Unlike general project management or terminal multiplexers, it offers a visual, multi-workstream interface with real-time notifications and a REST API for agent integration. It is suited for users needing to coordinate several AI agents efficiently, with a focus on automation and minimal manual oversight.

Key features

• Multiple parallel workstreams, each representing an autonomous agent session
• Queue tasks with detailed instructions and assign them to agents
• Autonomous agents pull, execute, and report back on tasks
• Notification system alerts when human input is required
• Secure API key management for connecting custom or third-party agents
• Supports self-hosted and open-source agents via REST protocol

Use cases

Managing parallel feature development across front-end, API, and testing teams by queuing tasks for each agent session.

Overnight backlog processing where multiple small tasks are assigned to different agents, with notifications for any manual decisions needed.

Refactoring large codebases while simultaneously shipping new features, with separate agent workstreams for each activity.