ACO System: Multi-Agent AI Pipeline from GitHub Issue to Merged PR

ACO System is a multi-agent framework that automates the full software development pipeline from GitHub Issue to merged pull request. It uses six specialized AI agents working independently through a shared database — no agent-to-agent communication, no dropped context.
Pipeline Overview
- PM Agent writes the user story from an issue.
- Planner Agent breaks the story into tasks with estimates.
- Architect Agent validates feasibility with a deterministic gate (no LLM, no hallucination risk).
- Developer Agent creates a branch, writes code, and opens a PR.
- QA Agent reviews the PR and runs tests.
- Human gives final sign-off before merge.
Key Design Decisions
Unlike LangChain, AutoGen, or CrewAI, the agents do not talk to each other. They all read and write through a shared database. Each agent runs independently. Complexity stays in the schema, not the logic.
Deterministic Architect Gate
The Architect gate is the feature the author is most proud of: it scans for hardcoded secrets, missing acceptance criteria, and invalid tech stack config. If anything fails, the story never reaches a developer — zero bad PRs.
Tech Stack
- Backend: Python
- Frontend: Next.js
- Database: SQLite in dev, Postgres in prod
- UI: Live Kanban dashboard and streaming event feed to watch agents in real time
Who It's For
Developers building in the agentic tooling space who want a practical, no‑babysitting pipeline that produces real artifacts.
The project is open source on GitHub: github.com/aniketkarne/aco-system
📖 Read the full source: r/openclaw
👀 See Also

SkyClaw: Rust-Based Autonomous AI Agent Runtime
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