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reyn

LLM workflow OS — phase transitions as a constrained decision graph.

reyn runs LLM workflows as a state machine. Phases are stateless and reusable; the workflow definition specifies the graph and the final output schema; the OS controls execution. The LLM's role is reduced to choosing among OS-provided transitions and producing structured artifacts — never to inventing control flow.

Where to start

If you want to... Go to
Install and start the agent Getting started
Solve a specific problem (chat user) Guide / for users
Understand the design Concepts
Read reyn through agent-engineering lenses Six lenses
Contribute See docs/deep-dives/contributing/ in the repository

The four reading modes (Diátaxis)

  • Guide — task-oriented. Getting started for onboarding, for users for chat-mode usage.
  • Reference — information-oriented. Look up and leave.
  • Concepts — understanding-oriented. The "why" of reyn.

Project status

reyn is in alpha (0.1.x). The DSL, CLI, and event log are stable enough to build workflows against, but APIs may still shift. Changelog and roadmap pages are coming in a later docs phase (changelog.md, architecture/roadmap.md).

Powered by AI

Reyn is powered by AI in two senses:

  • At runtime. Every workflow execution delegates decisions to an LLM provider via LiteLLM. Reyn is an LLM workflow OS by design.
  • In its development. Substantial portions of the codebase, the stdlib components, this documentation, and the landing page were drafted with AI tooling — primarily Claude Code (Anthropic) for implementation and Claude Design for the website. Human review, integration, and final architectural calls live with the maintainer; AI contributions are recorded as Co-Authored-By: Claude ... trailers in the git history.

This is a transparency note, not a marketing line. For provenance auditing, see git log --grep="Co-Authored-By: Claude" and the design prompts under website/_design/.