Tycono is an open-source, local-first framework for building and orchestrating multi-agent AI organizations, conceptualized as 'Company-as-Code'. It allows users to define AI agents, roles, and company hierarchies using declarative YAML and Markdown configurations, then watch them autonomously plan, execute, and learn from complex tasks. The system features a terminal-native user interface (TUI) for real-time supervision and manages persistent knowledge across sessions. The client library, `tycono`, is currently at version 0.3.44 and is under active development with frequent minor releases. Its companion, `tycono-server`, reached its first production-ready stable release at v0.1.0, providing a headless API backend. Key differentiators include its cost-efficiency features like 'Auto-Amend' for reducing LLM usage, and its ability to simulate and run entire AI companies for autonomous research and development.
npm install tyconoVerified import paths — ran on the pinned version, not inferred.
This quickstart demonstrates how to programmatically define an AI company with distinct roles and agents using assumed Tycono SDK APIs. It then initiates an autonomous task for the company, showcasing how to leverage LLMs (specifically Claude) for multi-agent collaboration. This example assumes 'tycono-server' is running to orchestrate the agents and requires an Anthropic API key.
Review the latest documentation or `npx tycono` TUI for updated interaction patterns. Update any custom scripts or integrations to align with the new 'Multi-Wave' and 'Dual Mode' concepts.
Examine the changelog between v0.2.0 and v0.3.10 for specifics. Migrate any custom code from 'Job'-centric paradigms to the new 'Session'-centric approach.
Ensure `tycono-server` (available as a separate npm package) is installed and running, and that necessary LLM API keys (e.g., `ANTHROPIC_API_KEY`) are correctly set in your environment.
Thoroughly validate your YAML/Markdown configuration files against the schema or examples provided in the official documentation. Use linters or schema validators if available.
Start the `tycono-server` in a separate terminal (`npm install -g tycono-server && tycono-server start`) or ensure the `TYCONO_SERVER_URL` environment variable points to the correct address if it's not local.
Set the `ANTHROPIC_API_KEY` environment variable with your valid Anthropic API key before running Tycono. For other LLMs, consult the specific documentation.
Inspect your agent/role configuration files for syntax errors or missing mandatory properties. Ensure all required fields, such as `id`, `name`, `level`, `model`, etc., are present and correctly formatted.
Use a modern terminal emulator (e.g., iTerm2, Kitty, Alacritty, VS Code integrated terminal) that supports 256 colors. Ensure your `TERM` environment variable is correctly set (e.g., `xterm-256color`).