GoKawiilOptio
Workflow orchestration for AI coding agents, from task to merged PR.
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.
Dashboard — real-time overview of running agents, pod status, costs, and recent activity
Task detail — live-streamed agent output with pipeline progress, PR tracking, and cost breakdown
How It Works
You create a task Optio runs the agent Optio closes the loop ───────────────── ────────────────────── ────────────────────── GitHub Issue Provision repo pod CI fails? Manual task ──→ Create git worktree ──→ → Resume agent with failure context Linear ticket Run Claude Code / Codex Review requests changes? Open a PR → Resume agent with feedback CI passes + approved? → Squash-merge + close issue
Intake — tasks come from the web UI, GitHub Issues (one-click assign), or Linear tickets Provisioning — Optio finds or creates a Kubernetes pod for the repo, creates a git worktree for isolation Execution — the AI agent (Claude Code or OpenAI Codex) runs with your configured prompt, model, and settings PR lifecycle — Optio polls the PR every 30s for CI status, review state, and merge readiness Feedback loop — CI failures, merge conflicts, and review feedback automatically resume the agent with context Completion — PR is squash-merged, linked issues are closed, costs are recorded
Key Features
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