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

✍️ OpenClawRadar📅 Published: June 5, 2026🔗 Source
ACO System: Multi-Agent AI Pipeline from GitHub Issue to Merged PR
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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.

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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

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👀 See Also