---
title: "Open Source | StudioMeyer"
description: "Our open source projects. Darwin, a TypeScript framework for self-evolving AI agents with A/B testing, multi-model critics, and safety gates."
canonical: "https://studiomeyer.io/en/open-source"
language: en
last_updated: 2026-09-14
image: "https://studiomeyer.io/en/open-source/opengraph-image?95302be4657d7529"
markdown_versions: ["https://studiomeyer.io/de/open-source.md", "https://studiomeyer.io/en/open-source.md", "https://studiomeyer.io/es/open-source.md"]
publisher: "StudioMeyer, https://studiomeyer.io (llms.txt: https://studiomeyer.io/llms.txt)"
---

Open Source

# Code that improves itself

We don't just build websites. We build the tools that make AI systems better. Open source. TypeScript. Runs in our own agent fleet.

[View on GitHub](https://github.com/studiomeyer-io/darwin-agents)[Learn more](#darwin)

Flagship Project

## Darwin Agents

A TypeScript framework for AI agents that improve their own prompts, automatically, without manual tuning. A critic scores every run. Better variants are A/B-tested with always-valid statistics. Anything that regresses rolls back. The key difference from other optimization approaches: the reflective loop runs continuously while agents work, not as a periodic batch job.

TypeScriptMIT LicenseMulti-ProviderSQLite + PostgreSQL

0

Hard deps

456

Tests

MIT

License

[GitHub](https://github.com/studiomeyer-io/darwin-agents)[npm](https://www.npmjs.com/package/darwin-agents)

terminal

```
# Install
npm install darwin-agents

# Run your first self-evolving agent
npx darwin run writer \
  "Explain quantum computing simply"

# Watch it evolve
npx darwin evolve writer
→ Pattern detected: market topics below target
→ New variant: writer-v2 generated
→ A/B test: v2 wins (7.12 vs 6.89 / 10)
✓ writer-v2 is now default
```

Self-Evolution

Agents detect weakness patterns and automatically generate improved prompt variants.

A/B Testing

New variants are tested against the current version. The winner becomes the default.

Safety Gates

Every evolution passes through quality gates. No uncontrolled prompt drift.

Multi-Provider

Use any model. Claude, OpenAI, Ollama, or your own. Darwin doesn't lock you into a provider. Swap the model, keep the evolution loop.

How it works

## The Evolution Loop

Darwin improves AI agents automatically. No manual prompt engineering required.

1

Agent runs a task

Your agent handles an assignment, writing, researching, analyzing.

2

Critics evaluate quality

Specialized critic agents measure quality, sources, structure, and relevance.

3

Patterns emerge

After enough runs, Darwin detects patterns: 'weak on technical topics', 'too verbose in summaries'.

4

New variant is generated

An optimizer generates an improved prompt variant based on detected patterns.

5

A/B test decides

The new variant is tested against the current version. Blind, fair, data-driven.

6

Winner becomes default

The better variant takes over. Your agent got better, automatically.

Get involved

## Built in the open, because that's how you earn trust

Darwin is MIT-licensed. We publish the source, the tests, and the results. Issues and pull requests are welcome.

[View Repository](https://github.com/studiomeyer-io/darwin-agents)[Get in touch](https://studiomeyer.io/en/contact)

## Sitemap

Every page of this site as Markdown: [sitemap](https://studiomeyer.io/sitemap.md). Curated entry point: [llms.txt](https://studiomeyer.io/llms.txt).