AI Agent to create sesison

 

Summary

This video is tailored for non - technical users who regularly use AI tools. It explains AI agents through a three - level learning path. Starting with large language models (LLMs), it shows their limitations like limited proprietary knowledge and passivity. Then it moves on to AI workflows, which follow predefined paths set by humans, with retrieval augmented generation (RAG) as an example. Finally, it introduces AI agents, where an LLM replaces the human decision - maker, reasoning, acting, and iterating autonomously to achieve a goal.

Abstract

The video aims to demystify AI agents for those with no technical background. It begins by introducing large language models, which are the foundation of popular chatbots. LLMs are great at text generation but have two significant drawbacks: they lack access to proprietary information and are passive, waiting for human prompts.

Next, the concept of AI workflows is explored. By adding logic to an LLM, it can perform actions like accessing a calendar or weather data. However, AI workflows are restricted to predefined paths set by humans. The video also clarifies that retrieval augmented generation (RAG) is a type of AI workflow. A real - world example of creating social media posts using make.com is provided to illustrate how AI workflows operate.

Finally, the video delves into AI agents, the most advanced level. The crucial difference between an AI workflow and an AI agent is that in an AI agent, the LLM takes over the role of the human decision - maker. It can reason about the best approach, act using tools, and iterate autonomously to improve the output until the goal is achieved. Real - world examples of AI agents are given to demonstrate their functionality.

Main Points

1. Large Language Models (LLMs):
   • Foundation of popular chatbots like ChatGPT, Google Gemini, and Claude.
   • Limited knowledge of proprietary information.
   • Passive, waiting for human prompts.
2. AI Workflows:
   • Follow predefined paths set by humans.
   • RAG is a type of AI workflow that helps AI models look up information.
   • Can be created using tools like make.com, as shown in the social media post example.
3. AI Agents:
   • LLM replaces the human decision - maker.
   • Can reason, act, and iterate autonomously to achieve a goal.
   • Examples include Andrew's demo website and the author's own basic AI agent under development.