How I Made AI Assistants Do My Work For Me - CrewAI

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AI Summary

Summary: AI Assistants and Rational Thinking

• Contemplating a Purchase:
  • Internal debate over buying trendy shoes.
  • Concerns about personal taste and being a trendsetter.
  • Decision-making process interrupted for a snack.
• System 1 and System 2 Thinking (Daniel Kahneman):
  • System 1: Fast, subconscious, automatic (e.g., recognizing faces).
  • System 2: Slow, conscious, deliberate (e.g., complex decision-making).
• AI and Thinking Systems:
  • Current AI models exhibit only System 1 thinking.
  • AI lacks the ability to engage in System 2 thinking like humans.
• Simulating Rational Thinking in AI:
  • Method 1: Tree of thought prompting (multiple perspectives).
  • Method 2: Platforms like Crew AI and agent systems (collaborative AI agents).
• Building AI Agent Teams with Crew AI:
  • Non-programmers can build custom agents.
  • Agents can access real-world data (emails, Reddit).
  • Local models can be run to avoid fees and protect privacy.
• Example: Startup Concept Analysis:
  • Setting up agents in VS Code for market research, technology, and business development.
  • Agents perform tasks sequentially, building on each other’s output.
  • Results include a business plan with detailed strategies and goals.
• Improving AI Agent Intelligence:
  • Adding tools for real-time data access (e.g., Lang chain tools).
  • Custom tools for specific data sources (e.g., Reddit scraping).
• Newsletter Creation with AI Agents:
  • Agents tasked with creating a detailed report in blog/newsletter format.
  • Challenges with data quality and adherence to instructions.
  • Variability in AI performance and output.
• Cost and Privacy Considerations:
  • API calls to models like GPT-4 can be expensive.
  • Running local models can save costs and enhance privacy.
• Testing Local Models:
  • Performance varies across different models.
  • Some models struggle with understanding tasks.
  • Best performing model was able to incorporate Reddit data into output.
• Resources:
  • GitHub notes on local models and code examples provided.

For more details on the process and results of using AI to simulate rational thinking and build agent teams, you can refer to the provided GitHub link.