Introduction

This is a curated list of high-quality resources for building and understanding agentic AI systems. Inspired by GitHub’s “awesome” lists, this collection includes tutorials, guides, and practical frameworks that I’ve found particularly valuable for developing AI agents.

Video Tutorials

Building Effective Agents with LangGraph

Link: https://youtu.be/aHCDrAbH_go?si=bhfrdA1zS0Q2DqgL

A comprehensive video tutorial on building agents using LangGraph, covering practical implementation details and best practices.

Ask David: Multi-Agent AI for Investment Research - JP Morgan Chase

Link: https://www.youtube.com/watch?v=yMalr0jiOAc

From LangChain’s Interrupt conference, David Odomirok and Zheng Xue from JP Morgan Chase Private Bank demonstrate “Ask David” - a sophisticated multi-agent AI system that automates investment research for thousands of financial products. This enterprise-grade system showcases how to build AI agents with human oversight for high-stakes financial decisions involving billions in assets.

Written Guides

Building Effective Agents - Anthropic

Link: https://www.anthropic.com/engineering/building-effective-agents

Anthropic’s engineering guide on building effective AI agents. This resource provides insights from the creators of Claude on agent design patterns, common pitfalls, and architectural considerations.

A Practical Guide to Building Agents - OpenAI

Link: https://cdn.openai.com/business-guides-and-resources/a-practical-guide-to-building-agents.pdf

OpenAI’s practical guide offering a business-oriented perspective on building AI agents. This PDF covers use cases, implementation strategies, and considerations for deploying agents in production environments.

Tools & Applications

LangGraph Flow Designer

GitHub: https://github.com/mrwadams/langgraph-flow-designer
Live App: https://langgraph-flow-designer.vercel.app/

A visual flow designer I created for building and managing LangGraph workflows. This interactive tool provides a drag-and-drop interface for designing complex graph-based AI workflows, featuring grid snap alignment, multiple node types (regular, START, END, subgraph), conditional edge connections, and JSON export/import capabilities. Built with React and Vite, it simplifies the process of designing sophisticated AI agent workflows by providing an intuitive visual development environment.

This list will be updated as I discover new valuable resources. Feel free to suggest additions via GitHub issues