In this talk, we’ll learn to build our own custom AI Agent.
We’ll start by answering a few basic but important questions: What is an agent? How does it “think”? What do we mean by tools, models, and memory in this context? From there, we’ll go hands-on.
In this demo will use Agno, a full-stack open-source framework for building AI agents with tools, memory, and reasoning, and Streamlit for a minimal user interface. I’ll walk through how I created a custom agents using Agno:
Agents that are not just chatbots but also for scraping, analysis, automation, and domain-specific assistants that use external knowledge bases, depending on your needs.
How to choose a model
How to add tools (e.g. stock data, search APIs)
How to give the agent clear instructions
How to use memory or build a team of agents when needed
I’ll show live how everything connects together in the Streamlit app, from tool setup to the agent responding intelligently to real-world queries.
We’ll also discuss what can break (like bad tool responses, unclear goals), how to debug those issues, and what kinds of tasks agents are actually useful for.
This is not a high-level overview, it’s a grounded, hands-on session for anyone curious about building functional agents using opensource tools. If you've seen demos of “AI assistants” and wondered how they’re built, this talk will show you exactly that, with real code and zero marketing. You don’t need any prior experience with AI or ML, just a basic understanding of Python is enough to get started.
