evogit

Decentralized Code Evolution via Git-Based Multi-Agent Collaboration

EvoGit: 1st Place in AgentX Multi-Agent Track

Winner of the Multi-Agent Track at the AgentX Competition (Agentic AI Summit).

[!IMPORTANT] EvoGit has evolved into EvoX Genesis — the successor project, born out of EvoGit! The new home of this work is https://github.com/EMI-group/genesis — follow it for all the latest development, including our landmark achievement of scaling to hundreds of thousands of lines of code with zero human intervention — for just a few dollars.

Table of Contents

1. Overview
2. ✨ Key Features
3. Live Demos
4. How to Explore the Results
5. Paper

Overview

EvoGit is a decentralized multi-agent framework that reimagines software development as a collaborative, evolutionary process. It deploys a population of independent coding agents that evolve a shared codebase asynchronously, without centralized coordination, explicit message passing, or shared memory.

All coordination emerges implicitly through a Git-based phylogenetic graph that tracks the complete version lineage. This graph allows agents to read from and write to the repository, enabling scalable parallel exploration while preserving a consistent, auditable history of every change.

For detailed methodology and experimental results, refer to our paper.

✨ Key Features

• Decentralized Coordination: Agents operate independently and coordinate organically through the shared version graph. This resembles stigmergy in biological systems, where interactions are indirect and mediated by the environment.
• ⚙️ Git-Native Evolution: The entire framework is built on Git. Evolutionary concepts map directly to Git primitives, making the process inherently compatible with standard developer tools.
• Traceable & Auditable Lineage: Every edit, merge, and decision is recorded as an immutable Git commit. This provides full transparency and reproducibility of the entire development process.
• Sparse Human Oversight: The human's role shifts from a coder to a high-level Product Manager. You define initial goals and provide periodic, lightweight feedback to prune unproductive branches and promote promising ones.

Live Demos

Explore how EvoGit enables collaborative AI development across two real-world projects. For more details, please visit the respective GitHub repositories and inspect the Git history to see how multiple agents evolved the code.

Web Applicaiton Development -- link

A multi-agent AI system collaboratively builds a complete one-page interactive website—from layout and UI to animations and dark mode. The project was initialized by a human product manager and guided with ~10 feedback interventions.

The final web page demonstrates a polished UI with support for both light and dark themes.

Meta-Level Code Synthesis -- link

AI agents iteratively evolve a meta-level algorithm designer, which itself generates and refines a solver for the classic Bin Packing Problem. This creates a two-layer pipeline: EvoGit → Auto Algorithm Designer → Bin Packing Solver A human manager provided an initial setup and ~5 rounds of feedback throughout the optimization process.

The AI-generated automatic algorithm design program efficiently found a solver that minimizes bin usage, as shown in the final output script:

…

The optimized code is automatically saved as best_solution.py after the search process completes.

How to Explore the Results

EvoGit uses Git not only as a version control tool, but also as a transparent window into the code evolution process. Here's how to inspect our demos:

1. ‍ The human-initialized seed lives in the main branch.
2. AI-generated code lives in branches named: host<i>-individual-<j>, where i = host node index, j = agent index.
3. Each agent branch contains an independent development trajectory. You can explore these using GitHub’s commit history or local Git tools.
4. Git diffs and logs reveal the precise changes made in each commit.
5. Use git log --graph or GitHub’s branch visualization (under Insights -> Network) to see how code diverged and converged over time.

All changes are versioned and traceable. Every commit represents an autonomous decision by an agent—captured, auditable, and reproducible through Git.

[!NOTE] GitHub may hide some branches. Click “View all branches” on the repo page to see the complete version graph.

Paper

Read the full framework design, evaluation methodology, and results in our paper:

• ArXiv:2506.02049

Current Status

EvoGit has evolved into EvoX Genesis!

Born out of EvoGit, the successor project has achieved something truly incredible: scaling to hundreds of thousands of lines of code with zero human intervention — for just a few dollars.

Follow the new repository at https://github.com/EMI-group/genesis for the latest development, releases, and updates. The journey continues there!