Tycono: Open-Source AI Agent Harness with Org Chart and Autonomous Improvement Loops
Tycono is an open-source harness that lets you define AI agent roles in YAML format (CTO, engineer, QA, etc.) and have them work together following an organizational chart. The system was built over about 3 weeks using Claude Code as a side project.
How It Works
You define agent roles in YAML configuration files, specifying different roles like CTO, engineer, QA, and CBO. These agents don't just complete tasks and stop - they operate with a CEO Supervisor loop that reviews results, asks C-level agents "what can be improved?", and automatically re-dispatches tasks for refinement.
Example Workflow
When given the directive "build a pixel running game," the system demonstrated this workflow:
- CTO designed the architecture and broke it into tasks
- Engineer built the core functionality: running, jumping, obstacles, hearts
- QA opened a real Chrome browser and tested every collision
- CBO analyzed the game and suggested "add a Shop system, it'll improve retention"
- CTO took the feedback, redesigned the architecture, and the cycle restarted
The CBO's business perspective is notable because it's something pure engineering-focused agents wouldn't have produced.
Performance Metrics
In an overnight test with the pixel running game task:
- 17 improvement rounds completed
- 6,796 lines of code generated
- 43 commits made
- 125 AI sessions executed
The system runs autonomously - the developer was sleeping during this process.
Key Insight
Each role genuinely thinks differently: CBO sees users, CTO sees architecture, QA breaks things. This isn't just 5 copies of Claude - the org chart structure gives them different perspectives and lenses through which to approach problems.
Getting Started
Install with: npx tycono
You can play the resulting game at: https://tycono.ai/pixel-runner.html
The source code is available on GitHub: https://github.com/seongsu-kang/tycono
📖 Read the full source: r/ClaudeAI
👀 See Also
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Qwen3.5-9B-Claude-4.6-Opus-Uncensored-v2 Model Released with LM Studio Configuration
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