Optio

Optio turns coding tasks into merged pull requests — without human babysitting. Submit a task (manually, from a GitHub Issue, or from Linear), and Optio handles the rest: provisions an isolated environment, runs an AI agent, opens a PR, monitors CI, triggers code review, auto-fixes failures, and merges when everything passes.

The feedback loop is what makes it different. When CI fails, the agent is automatically resumed with the failure context. When a reviewer requests changes, the agent picks up the review comments and pushes a fix. When everything passes, the PR is squash-merged and the issue is closed. You describe the work; Optio drives it to completion.

Key features:

• Autonomous feedback loop — auto-resumes the agent on CI failures, merge conflicts, and review feedback; auto-merges when everything passes
• Pod-per-repo architecture — one long-lived Kubernetes pod per repo with git worktree isolation, multi-pod scaling, and idle cleanup
• Code review agent — automatically launches a review agent as a subtask, with a separate prompt and model
• Per-repo configuration — model, prompt template, container image, concurrency limits, and setup commands, all tunable per repository
• GitHub Issues and Linear intake — assign issues to Optio from the UI or via ticket sync
• Real-time dashboard — live log streaming, pipeline progress, cost analytics, and cluster health