We built Sgai to experiment with a different model of AI-assisted development.

Instead of prompting step-by-step, you define an outcome in GOAL.md (what should be built, not how), and Sgai runs a coordinated set of AI agents to execute it.

- It decomposes the goal into a DAG of roles (developer → reviewer → safety analyst, etc.) - It asks clarifying questions when needed - It writes code, runs tests, and iterates - Completion gates (e.g. make test) determine when it's actually done

Everything runs locally in your repo. There’s a web dashboard showing real-time execution of the agent graph. Nothing auto-pushes to GitHub.

We’ve used it internally for prototyping small apps and internal tooling. It’s still early and rough in places, but functional enough to share.

Demo (4 min): https://youtu.be/NYmjhwLUg8Q GitHub: https://github.com/sandgardenhq/sgai

Open source (Go). Works with Anthropic, OpenAI, or local models via opencode.

Curious what people think about DAG-based multi-agent workflows for coding. Has anyone here experimented with similar approaches?