Broccoli: Open-source harness for running AI coding agents from Linear tickets in cloud sandboxes
What Broccoli does
Broccoli turns Linear tickets into shipped PRs by running AI coding agents in isolated cloud sandboxes. Each task gets its own sandbox where it checks out the repo, uses ticket context, implements solutions, runs tests and review loops, then opens a pull request for team review.
Architecture and deployment
The implementation uses:
- Webhook deployment: GCP
- Sandbox: GCP or Blaxel
- Project management: Linear
- Code hosting & CI/CD: GitHub
It's deployed to your own GCP project against your Postgres database with no third-party control plane. The deployment is production-grade using Cloud Run + Secret Manager + webhook deduplication + durable job state.
Key features
- Linear ticket → reviewable PR workflow
- Your infrastructure, keys, and data stay within your tenancy
- AI code review on every PR using Claude and Codex
- Customizable prompt templates that you can fork, tune, and version
- Deploys in ~30 minutes with one bootstrap script and one config file
Deployment prerequisites
To deploy, you need:
- GCP project with billing attached and
gcloudlogged in - GitHub App with specific permissions (Contents, Pull requests, Issues = read/write; Metadata = read-only; subscribed to Pull request review event)
- Linear bot user (dedicated, not personal account) with API key
- OpenAI and Anthropic API keys with billing enabled
- Linear webhook pointing at
${Service URL}/webhooks/linearusing auto-generatedbroccoli-oss-linear-webhook-secret
Usage results
In the last four weeks, 100% of PRs from non-developers were shipped via Broccoli. For developers on the team, this share is around 60%, with more complicated features requiring manual back-and-forth design with Codex/Claude Code.
📖 Read the full source: HN AI Agents
👀 See Also
Bifrost AI Gateway: Open-Source Tool Addresses AI Infrastructure Gaps
Bifrost is an open-source Go-based LLM gateway that provides automatic failover between providers, budget caps that reject requests, audit logging, and hooks for evaluation. Benchmarks show it's ~50x faster than LiteLLM at high throughput.
Multi-operator Claude Code: Hub-based architecture for multi-agent sessions
A hub-based setup for Claude Code enables multiple people to attach to the same session, route subtasks across repos, and run headless agents in Docker containers.
OpenClaw users report planning and review bottlenecks with AI agents
OpenClaw users describe planning and review workflows as 'MS-DOS-like' despite effective code generation, citing manual intervention, document fragmentation, and loss of reasoning during agent collaboration. Some are experimenting with agent-native document editors like comment.io and Proof by Every.
AI Agent Embedded in Shell: Terminal Buffer & Overlay Extension
Open-source shell with embedded AI agent that reads terminal output and types commands via a floating overlay. Supports local and cloud models.