Weekly, Sept. 10th – Oct. 15th
12:00pm PST – 1:00pm PST
Virtual
Dive into the world of AI agent development in this comprehensive bootcamp. You’ll gain hands-on experience with the latest tools and techniques in AI agent development. From understanding core architectures to troubleshooting complex issues, our expert-led sessions will equip you with the knowledge and skills to build sophisticated AI agents that can tackle real-world challenges. You’ll learn how to navigate popular frameworks, optimize performance, and evaluate your agents effectively.
Unit 1: Agent Architectures | On Demand
We’ll dive into the fundamental building blocks of agent-based systems, exploring different architectural models that enable efficient and scalable LLMs. We’ll cover core concepts like components, execution branches, and routers. We’ll also touch on how agents have evolved over the past few years.
Unit 2: Comparing Agent Frameworks | Sept. 17th
In this session, we’ll compare popular agent frameworks like LangGraph and LlamaIndex workflows, highlighting their strengths, weaknesses, and ideal use cases. You’ll gain insights into which framework best suits different projects and how to leverage them effectively.
Unit 3: Evaluating Agents | Oct. 1st
Now that we’ve covered how to create agents, it’s time to learn how to systematically evaluate the performance of these tools. Evaluating agents can be notoriously difficult, but with a bit of structure, it can be done. We’ll explore metrics, benchmarks, and tools that can help you assess performance and point to problem areas in your application
Unit 4: Is Your Agent Stuck in a Loop? | Oct. 1st
One of the trickiest areas of evaluating agents is identifying when they’ve entered into excessive loops, and breaking them out of those loops. In this session, we’ll cover techniques for identifying, diagnosing, and resolving these looping issues, and help you create truly optimized agents.
Unit 5: Task Decomposition for Smarter Agents w/ Jerry Liu (LlamaIndex) | Oct. 8th
We’re excited to be joined by Jerry Liu, Co-Founder & CEO of LlamaIndex as we explore how to break down complex tasks into manageable components that your agents can handle. We’ll discuss strategies for task decomposition, ensuring your agents can perform efficiently and accurately, as well as common task compositions for typical types of agents and assistants.
Unit 6: AutoGen: From Architecture to Optimization | Oct. 15th
We’re excited to be joined by Chi Wang, founder of AutoGen, to discuss this multi-agent framework for enabling next-gen AI applications.