Ever wondered what "Agentic AI" really means? I decided to build one from scratch to find out. In this video, I give a full demo and code walkthrough of my first Agentic AI project, built with Python, Google Gemini, and a whole toolbox of capabilities!
This isn't just theory. We'll see the agent in action as it performs multi-step tasks, and I'll break down exactly how the "Think, Act, Observe" loop works behind the scenes. Whether you're a developer or just curious about AI, this video will show you the core philosophy of agents.
1. Watch the AI agent use Web Search (SerpApi) and the File System to solve a complex task in real-time.
2. A visual animation (made with Manim) that breaks down the "Think-Act-Observe" loop, the heart of any AI agent.
3. A deep dive into the `simpleagent.py` code, explaining how the different components work together.
4. How I implemented persistent, long-term memory using a FAISS vector database so the agent never forgets.
5. A look at the tools that allow the agent to read and write files, interacting with its environment.
6. Understanding the main `run` function that orchestrates the entire process from task to final answer.
7. A sneak peek at the next step: integrating the Model-Context-Protocol (MCP) for even more advanced capabilities.
If you found this video helpful, please give it a thumbs up and subscribe to the channel for more projects like this! Let me know in the comments what tools I should add next.
https://www.youtube.com/watch?v=XcMgzJ6P7nA
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