Inspiration

As AI agents become more capable, people still struggle to decide which tasks should be automated, delegated to AI, or handled by humans.

We wanted to build an operating system where humans and AI collaborate naturally instead of competing. Inspired by modern AI agent workflows, Magent helps teams focus on high-value work while AI takes care of repetitive and time-consuming tasks.

What it does

Magent is an AI-native workforce operating system.

It allows users to create tasks, assign them to AI agents or human teammates, monitor progress, and manage collaboration from a single workspace.

Depending on the task, Magent can recommend whether it should be completed by an AI agent, a human, or a hybrid workflow where both work together.

How we built it

We built Magent using GPT-5.6 and Codex throughout the development process.

Codex accelerated implementation, debugging, and code refactoring, while GPT-5.6 helped design workflows, improve reasoning, and iterate on product architecture.

The application combines a modern web interface with backend services that coordinate task management, AI decision making, and collaborative workflows.

Challenges we ran into

The biggest challenge was designing workflows that feel natural instead of forcing AI into every task.

We also spent significant time improving task routing, collaboration flows, and keeping the overall experience simple while supporting increasingly complex agent interactions.

Accomplishments that we're proud of

We're proud of creating a practical foundation for human-AI collaboration rather than another standalone chatbot.

Magent demonstrates how AI agents can become productive teammates while keeping humans responsible for important decisions.

What we learned

This project taught us that successful AI products are not just about model capability.

The user experience, workflow design, and clear collaboration between humans and AI are equally important for building something people actually want to use.

What's next for Magent

Next, we plan to support multiple specialized AI agents, richer collaboration tools, long-term memory, integrations with external services, and autonomous workflows that can complete complex multi-step tasks with minimal human supervision.

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