OpenHands Agent Canvas: Turn Your Coding Agents Into a Self-Hosted Engineering Team

Intro
You've probably seen demos of AI coding agents editing files, running commands, and fixing bugs. They're cool, but they usually work solo. What if you could have a whole team of these agents working together, each with a different role, all inside your own infrastructure?

That's the idea behind OpenHands Agent Canvas (part of the OpenDevin project). It lets you orchestrate multiple AI agents to act as a self-hosted engineering team. No cloud lock-in, no rate limit headaches. Just agents that plan, code, review, and deploy like a real squad.

What It Does
OpenHands Agent Canvas is a platform where you define a "canvas" of agents. Each agent has a specific role (e.g., "Frontend Developer", "Code Reviewer", "DevOps Engineer") and can communicate with others. You give them a high-level task, and they break it down, work in parallel, and hand off results to each other.

Under the hood, it's a Python framework that manages agent lifecycle, tool access, and inter-agent messaging. It integrates with any LLM (OpenAI, Anthropic, local models) and runs entirely on your hardware or VPS.

Why It’s Cool

• Self-hosted – No sending your code to a third-party API. Agents run locally, using tools like bash, git, and editor on your machine.
• Role-based orchestration – Assign agents different personas. A "Planner" agent writes specs, a "Coder" implements them, a "Reviewer" checks for bugs. They form a mini agile team.
• State persistence – Agents remember context across sessions. You can pause work and resume days later.
• Customizable tools – Give agents access to your database, APIs, or Docker containers. They can run migrations, deploy services, or run tests automatically.
• Visual canvas UI – See agent conversations, task progress, and outputs in a real-time dashboard (optional, but helpful for debugging).

How to Try It
The repo is at github.com/OpenDevin/OpenDevin.

1. Install – pip install opendevin (Python 3.10+).
2. Set up – Create a config.toml with your LLM provider (e.g., local Ollama or OpenAI API key).
3. Run – opendevin canvas start to launch the UI, or use the Python API to script agent teams.
4. Example – The repo has a "build a todo app" demo where three agents (planner, coder, reviewer) collaborate from scratch.

For a quick taste, check the examples/ folder on GitHub.

Final Thoughts
This is still early (v0.3 at time of writing), but the concept is promising. If you're tired of single-agent limitations or want to experiment with AI coordination patterns, OpenHands is worth a look. It's especially fun for CI/CD pipelines, prototype generation, or just watching two agents argue about code style.

If you try it, let us know how your agent team performs.

Found this on @githubprojects