Open source · MIT licensed

From ticket to
merged PR.

Optio orchestrates AI coding agents through the full development lifecycle. Submit a task, and it handles execution, CI monitoring, code review, and merge — automatically.

Up and running in minutes

terminal

$ git clone https://github.com/jonwiggins/optio.git

$ cd optio

$ ./scripts/setup-local.sh

# Dashboard at http://localhost:30310

# API at http://localhost:30400

Requires Docker Desktop with Kubernetes enabled. Full installation guide →

The complete task lifecycle

Every task flows through a seven-stage pipeline. Optio monitors each stage and automatically drives the task forward.

Intake

GitHub Issue, Linear, or manual

Queued

Enters the pipeline

Provisioning

Find or create pod

Running

Agent writes code

PR Opened

Opens pull request

CI & Review

Checks & feedback

Merged

Squash-merge & close

The feedback loop is
what makes it different.

Optio doesn't just run an agent and walk away. It watches the PR, feeds failures back to the agent, and keeps going until the work is done.

CI failsResume agent with failure context
Merge conflictsResume agent to rebase
Review requests changesResume agent with feedback
CI passes + approvedSquash-merge & close issue
task lifecycle

Task created from GitHub Issue #142

Queued, waiting for pod...

Running claude-sonnet-4-6 in worktree

PR #87 opened against main

CI failed: lint errors in auth.ts

Resuming agent with CI context...

CI passed, all checks green

Review requested, awaiting approval

Review: "add error handling for edge case"

Resuming agent with review feedback...

CI passed, review approved

PR #87 squash-merged, Issue #142 closed

Everything you need to orchestrate AI agents

Built for teams that want to scale AI-assisted development without the manual overhead.

Autonomous Feedback Loop

CI fails? Agent resumes with failure context. Reviewer requests changes? Agent picks up the comments and pushes a fix. It keeps going until the PR merges.

Pod-per-Repo Isolation

One long-lived Kubernetes pod per repo with git worktree isolation. Multiple tasks run concurrently in separate worktrees. Idle pods clean up automatically.

Multi-Agent Support

Run Claude Code or OpenAI Codex. Configure model, prompt template, and settings per repository. Launch review agents as subtasks with separate prompts.

GitHub & Linear Intake

Pull tasks from GitHub Issues, Linear tickets, or create them manually. One-click assign from the web UI kicks off the full pipeline.

Real-time Dashboard

Live log streaming, pipeline progress visualization, cost analytics, and cluster health monitoring. Watch your agents work in real time.

Self-Healing Pipeline

Auto-resume on CI failures, merge conflicts, and stale tasks. Auto-merge when CI passes and review is approved. Close linked issues on completion.

Built for production

Fastify API, Next.js dashboard, BullMQ workers, Drizzle on Postgres. Ships with a Helm chart for Kubernetes deployment.

Web UI

Next.js · :3100

Dashboard
Tasks
Repos
Cluster
Costs
API Server

Fastify

Workers

Task Queue
PR Watcher
Health Mon
Ticket Sync

Services

Repo Pool
Review Agent
Auth / Secrets
Kubernetes

Repo Pod A

worktree 1
worktree 2
worktree N

Repo Pod B

worktree 1

= Claude Code / Codex

Postgres + Redis
TasksLogsEventsSecretsJob queuePub/subLive streaming

Open source. Deploy on your infrastructure.

Optio is fully open source under the MIT license. Deploy on your own Kubernetes cluster with the Helm chart and start orchestrating AI agents in minutes.