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

TL;DR

Learn how to assemble a team of smart AI agents to solve complex problems using tools like crewAI and agent systems, and how to make them even smarter by incorporating real-world data.

Transcript

have you ever found yourself on the verge of making a controversial purchase just as you're about to click on that buy button an unexpected thought suddenly crosses your mind wait a minute they look a little bit like soy cheese don't they no no no no no they're absolutely beautiful and Kanye West loves them he wears them all the time but if I like ... Read More

Key Insights

• 🤔 System thinking, which involves conscious and deliberate effort, is the type of rational thinking that we want from AI.
• 🤔 Large language models (LLMs) currently only possess system one thinking, which is subconsciously and automatically recognizing familiar patterns.
• 💭 Simulating rational thinking in AI models can be achieved through tree of thought prompting or utilizing platforms like crewAI and agent systems.
• 👻 crewAI allows the creation of custom AI agents, who can collaborate and solve complex tasks.
• 🔨 Making AI agents smarter can be done by incorporating real-world data using tools like Gemina or writing custom tools to scrape specific sources of information.
• 🤙 Local models can be used to run AI models locally, avoiding costly API calls and ensuring privacy.
• ❓ The performance of different local models varies, with some models failing to understand the task and others producing more desirable results.
• ❓ Experimentation and fine-tuning are necessary to achieve the desired output from AI agents.

Questions & Answers

Q: What is system thinking and how does it relate to AI assistance?

System thinking is a conscious and deliberate type of thinking that requires effort and time to make rational decisions. In AI assistance, it refers to the ability of AI models to analyze problems from various angles and offer rational solutions.

Q: How can rational thinking be simulated in AI models?

There are two methods to simulate rational thinking in AI models. One is tree of thought prompting, where the model is forced to consider an issue from multiple perspectives or experts' viewpoints. The other method involves utilizing platforms like crewAI and agent systems to build a team of AI agents that can collaborate and solve complex tasks.

Q: What is crewAI and how can it be used to build a team of AI agents?

crewAI is a platform that allows anyone, even non-programmers, to build their own custom AI agents. Users can assign roles and tasks to these agents, who can collaborate with each other to solve complex problems.

Q: How can AI agents be made smarter by incorporating real-world data?

AI agents can be made smarter by giving them access to real-world data, such as emails or Reddit conversations. This can be done using tools like Gemina, which fetches Google search results, or by writing custom tools to scrape specific sources of information.

Summary & Key Takeaways

• The video discusses the concept of system thinking, where conscious and deliberate effort is required to make rational decisions, and how it relates to AI assistance.

• It introduces two methods to simulate rational thinking in AI models: tree of thought prompting and utilizing platforms like crewAI and agent systems.

• The video provides a step-by-step guide and examples on how to build a team of AI agents using crewAI, assign roles and tasks to them, and make them smarter by incorporating real-world data.