Inside an LLM Agent: A From-Scratch Walkthrough

Everybody's talking about AI agents. But what's actually inside one when you strip away the framework?

In this talk, Val Andrei Fajardo (author of the upcoming Manning Publications book, Build a Multi-Agent System (From Scratch) and ex-founding engineer at LlamaIndex) walks through the internals of an LLM agent from scratch. No CrewAI, no LangGraph, no black boxes. Just the raw building blocks: tool abstraction, the agent processing loop, MCP integration, and the Agent Skills open standard (plus a sneak peek at the upcoming memory chapter).

Through live examples, you'll see exactly what's happening under the hood of the agent clients you use every day, and how to build it yourself.

Val Andrei Fajardo

Val Andrei Fajardo is an AI engineer and scientist specializing in LLM agents and AI infrastructure. He is currently Principal AI Engineer and Researcher on the AI and Data Leadership Team at The Carlyle Group. He is a former founding engineer at LlamaIndex, where he contributed to and maintained their popular open-source Python framework that receives millions of downloads per month. After LlamaIndex, he worked as a researcher at the Vector Institute for AI, where he developed FedRAG, an open-source library for federated fine-tuning of RAG systems, which was accepted into the CODEML workshop at ICML 2025. Andrei holds a PhD in Statistics and Applied Probability from the University of Waterloo.