AI Self EVOLUTION (Meta Harness)

---
name: ai-self-evolution-meta-harness
version: "1.0.0"
description: "Self-evolving AI harnesses for LLMs"
source: "https://www.youtube.com/watch?v=61JUHDK-em8"
tags: [Cursor, Factory]
---

# AI Self EVOLUTION (Meta Harness)

> Auto-generated from: AI Self EVOLUTION (Meta Harness) by Matthew Berman

## Prerequisites
- Python 3.8+
- Access to an LLM API (e.g., OpenAI, Cohere)
- Basic understanding of LLMs and prompt engineering
- Familiarity with coding and software development principles

## Quick Start
1. `1.  Create a directory for your project: `mkdir meta_harness``
2. `2.  Navigate to the project directory: `cd meta_harness``
3. `3.  (Optional) Initialize a virtual environment: `python3 -m venv venv``
4. `4.  (Optional) Activate the virtual environment: `source venv/bin/activate``
5. `5.  Install necessary dependencies (e.g., LLM libraries): `pip install <llm_library> <other_dependencies>``
6. `6.  Create a `.env` file based on the `.env.example` and fill in the required values.`
7. `7.  Set up the initial harness code in the specified `HARNESS_PATH`.`
8. `8.  Create the evaluation script at the specified `EVALUATION_SCRIPT`.`

## What You Get
- Content Type: hybrid
- Difficulty: intermediate
- Tools: Cursor, Factory