GitHub - portpowered/you-agent-factory: Agent factory workflow engine for agents

infinite-you

infinite-you is an AI agent factory for scheduling and orchestrating concurrent AI work—the you CLI and dashboard let you run many agents at once instead of babysitting each task manually.

Why?

Leverage.

With infinite-you, you codify your process into a workflow with different AGENTS.md files and run them as wrappers around OpenAI Codex or other agent backends.

For example:

dispatch many agents to run independently in separate worktrees
have one agent loop through a series of tasks, then route output to a reviewer that re-queues failed work
submit plans in dependency order
use cron triggers to autonomously inspect git tasks and drive write/review cycles

Installation

Prerequisites

Codex CLI (default agent backend for the starter factory): npm i -g @openai/codex
A project directory where you want the local factory/ scaffold to live

Install the `you` CLI

macOS / Linux:

curl -fsSL https://github.com/portpowered/you-agent-factory/releases/latest/download/install.sh | sh

Windows (PowerShell):

irm https://github.com/portpowered/you-agent-factory/releases/latest/download/install.ps1 | iex

For custom install locations or pinned versions, see the install script.

Quick start

The default path uses the Codex-backed starter scaffold:

cd your-project-directory
Run you — bootstraps ./factory, starts the runtime, and prints the dashboard URL (usually http://localhost:7437/dashboard/ui)
Submit a task from the dashboard (for example, “write a report on my codebase to TEST.md”) and wait for completion

For factory authoring, CLI topics, and advanced setup, see Authoring factories and you docs.

Alternate executor: Claude

To scaffold a factory with Claude as the starter worker instead of Codex:

you init --executor claude --dir my-factory
you docs workstation

Features

infinite-you is a factory runtime: you define how work moves between workstations, and the you CLI plus dashboard schedule concurrent agent runs against that flow.

Concurrent agent execution — Run many agents at once across workstations; the dashboard shows live routing, session status, and factory flow state.
Workflow customization — Model processes as config (factory.json, workstation routes, AGENTS.md) instead of a fixed pipeline; adapt write/review loops, cron triggers, git worktrees, or other patterns to your repo.
Review loops — Route completed work to reviewer workstations and re-queue failed items; shipped factories such as Ralph and writer-reviewer demonstrate iterative plan/code/review cycles.
Batch submission — Submit single items from the CLI (you submit) or drive larger inputs through batch work types and dashboard submission.
Example factories — Load starter and advanced factories from examples/factories/ in the dashboard, or scaffold your own with you init.

Deeper product documentation:

Authoring factories — factory topology, workstations, workers, and customization workflow
CLI reference topics — you docs <topic> for config, work, sessions, workstations, and related guides
Architecture overview and data model — how factories, work, and runtime state fit together
Runnable examples — example factory directories and mock-worker inputs under docs/examples/

Comparison

How infinite-you fits next to nearby agent and workflow orchestrators. Dimensions focus on execution model, workflow flexibility, agent-harness support, and operational weight—not “best tool” claims. For a longer maintainer write-up, see Comparing orchestration systems.

System	Execution model	Workflow shape	Agent harness	Durability / ops weight	Reference
infinite-you	Self-hosted `you` runtime and dashboard route work through factory workstations	Custom in-repo flow (`factory.json`, `AGENTS.md`, routes) without a fixed pipeline	Codex, Claude, and shell workers wired through factory config	Lightweight local runtime; no built-in durable workflow engine	Architecture · Comparing systems
Gastown	Mayor-led multi-agent workspace with git-backed hooks and worktrees	Opinionated mayor/beads/convoy coordination around git	Hooks inject context into Claude Code, Copilot, Codex, and peers	Git/worktree persistence; heavier git + beads/dolt stack	Gastown
Symphony	Long-running orchestrator polls issue trackers and runs per-issue workspaces	Policy in-repo (`WORKFLOW.md`); spec-driven daemon workflow	Codex app-server sessions in isolated workspaces	Elixir daemon with supervision/retries; tracker-centric	Symphony
Factory	Droid Missions orchestrator with Mission Control for multi-day projects	Milestone/feature decomposition with validation contracts	Droid workers with MCP, skills, hooks, and custom droids	Productized orchestration with milestone validation loops	Factory Missions
8090 Software Factory	Hosted SDLC control plane (requirements → blueprints → work orders)	Upstream planning modules feed agents through MCP-connected work orders	External agents (Cursor, Claude Code, etc.) via MCP	Cloud platform with knowledge graph and audit trail	8090 docs
Claude workflow plugins	In-IDE Claude Code skills/commands drive spec → plan → execute loops	Plugin-defined task graphs, parallel dispatch, and worktrees	Native Claude Code subagents and skills	Session/task files on disk; no separate orchestration server	sighup/claude-workflow
Other orchestrators (Temporal, n8n, DBOS)	General-purpose durable or RPA workflow engines	DAG/state-machine or node graphs; often code- or node-config driven	Agent harnesses typically custom-built	Strong durability/transactions; heavier for ad-hoc agent loops	Comparing systems

References

Comparing orchestration systems — background on how infinite-you relates to nearby agent and workflow tools
Authoring factories — primary guide for defining and running factories
CLI reference index — packaged you docs topics and links to customer-facing guides
Work submission — you submit, batch inputs, and dashboard submission
Factory CLI — you factory query, save/list/update, and runtime factory management
Architecture and data model — factory execution model and persisted state
The zen of flow — design notes on work routing and factory composition
Example factories — drag-and-drop starter flows (doc reviewer, Ralph, timer, worktree, writer reviewer, and more)
Dashboard demo — animated view of concurrent agent dispatch

Maintainers: edit packaged reference docs under docs/reference/; run make docs-reference-smoke before shipping doc changes and make readme-check before changing README structure or linked assets.

License

This repository is released under the MIT License.

The README hero image (docs/internal/resources/dashboard.png) and the animated demo (docs/internal/resources/dashboard.gif) are screenshots maintained in this repository and depict the infinite-you dashboard UI.