MakeMoneyWithAI

🥈Silver

MakeMoneyWithAI provides a curated list of open-source AI projects for generating income. It benefits operations teams by offering tools for task automation, agent-based workflows, and extensible plugin integrations. Connects to Python-based workflows and supports Claude agents.

285480Updated 2mo ago

Intermediate30min to implementautomation

Saves ~30 min per use

Quick InstallView Source

git clone https://github.com/garylab/MakeMoneyWithAI.git

Works with:

Claude

Overview

About This Skill

How to Use

1. **Define Your Criteria**: Fill in the [PLACEHOLDERS] with your specific business goal (e.g., 'automate customer support'), technical stack (e.g., 'Python 3.9+'), and deployment environment (e.g., 'AWS EC2'). 2. **Run the Prompt**: Paste the completed prompt into your AI tool (Claude, ChatGPT, etc.) and execute it. For best results, use the latest version of the AI tool to ensure compatibility with MakeMoneyWithAI's curated list. 3. **Evaluate Projects**: Review the generated list and filter based on your priorities. Use the GitHub links to check project health (stars, recent commits, issues) and confirm compatibility with your stack. 4. **Plan Implementation**: For each selected project, create a timeline using the estimated setup times. Prioritize projects with the highest revenue potential and shortest setup times for quick wins. 5. **Test and Iterate**: Deploy a proof-of-concept for your top 1-2 projects in a staging environment. Use the revenue stream suggestions to validate monetization paths before full-scale implementation. **Tips**: - Combine multiple projects (e.g., LangChain + AutoGen) to create more complex workflows. - Check MakeMoneyWithAI's community forums for user reviews and implementation tips. - Use GitHub's 'Used By' section to see if other companies are successfully monetizing similar projects.

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/garylab/MakeMoneyWithAI

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Generate a personalized list of 5 open-source AI projects from MakeMoneyWithAI that align with [BUSINESS_GOAL] and [TECHNICAL_STACK]. For each project, include: project name, GitHub link, primary use case, estimated setup time, and potential revenue stream. Prioritize projects with active community support and clear monetization paths. Filter by [PROGRAMMING_LANGUAGE] compatibility and [DEPLOYMENT_ENVIRONMENT] requirements.

Example Output

Here are 5 open-source AI projects from MakeMoneyWithAI that align with your goal of automating customer support workflows using Python and deploying on AWS:

1. **ChatDev** (https://github.com/ChatDev/ChatDev)
   - Primary Use Case: End-to-end AI agent framework for building custom chatbots
   - Estimated Setup Time: 4 hours
   - Revenue Stream: Sell pre-built chatbot templates for e-commerce ($500-$2,000 per template)
   - Notes: Python-based, supports AWS Lambda deployment, 1.2k GitHub stars, last updated 2 weeks ago

2. **AutoGen** (https://github.com/microsoft/autogen)
   - Primary Use Case: Multi-agent conversation framework for task automation
   - Estimated Setup Time: 6 hours
   - Revenue Stream: Offer agent orchestration services ($1,500/month per client)
   - Notes: Microsoft-backed, Python 3.8+, AWS EKS compatible, 15k+ GitHub stars

3. **Rasa Open Source** (https://github.com/RasaHQ/rasa)
   - Primary Use Case: Custom NLP pipeline for intent recognition and entity extraction
   - Estimated Setup Time: 8 hours
   - Revenue Stream: Build and sell custom NLU models for niche industries ($3,000-$8,000 per model)
   - Notes: Python-based, Docker-ready, 18k+ GitHub stars, enterprise support available

4. **LangChain** (https://github.com/langchain-ai/langchain)
   - Primary Use Case: LLM integration framework for building AI-powered applications
   - Estimated Setup Time: 5 hours
   - Revenue Stream: Develop and license AI-powered document processing tools ($2,000-$5,000 per license)
   - Notes: Python 3.8+, AWS SageMaker compatible, 60k+ GitHub stars, weekly updates

5. **Hugging Face Transformers** (https://github.com/huggingface/transformers)
   - Primary Use Case: Pre-trained models for text classification and generation
   - Estimated Setup Time: 3 hours
   - Revenue Stream: Fine-tune models for specific use cases and sell API access ($0.01-$0.10 per API call)
   - Notes: Supports AWS SageMaker, 100k+ GitHub stars, active community forums

**Recommendation**: Start with AutoGen for agent orchestration as it directly addresses your customer support automation goal and has the highest revenue potential through service contracts. The setup time is reasonable, and the framework's flexibility allows for quick customization to your specific needs. Consider combining Rasa Open Source with LangChain to create a hybrid solution that handles both intent recognition and workflow automation.