Build Intelligent AI Apps: Build an Agent

From the creator

In this episode, Ayan Gupta is joined again by Julien Dubois, who takes AI development to the next level by showing you how to build multi-agent systems that work together. Imagine if your coffee cup could not only order a refill on its own but also coordinate with a barista to prepare it exactly how you like it, that's the power of AI agents working in concert! Building on the foundation from the last session, this session dives deep into creating three coordinated AI agents using LangChain4j. The first is an "Author" agent that writes poems using GPT-4o Mini. The second is an "Actor" agent that uses Mistral 3B and a text-to-speech tool called MaryTTS to transform poems into audio files. The third is a "Supervisor" agent that orchestrates the other two, ensuring they work together seamlessly. Julien explains the two fundamental approaches to agent orchestration: Pure AI orchestration, where a supervisor LLM decides which agents to call and when, and Workflow-based orchestration using LangChain4j's rich API to define sequences, loops, and parallel operations. For this demo, you'll use the simpler workflow approach with a SequenceBuilder that chains the Author and Actor agents together. The result? You ask for a poem about "Java Virtual Machine," and the system automatically generates the poem with one agent, converts it to speech with another, and delivers an output.wav file you can play. This demonstrates the incredible potential of multi-agent systems for complex, real-w

Published 2025-11-04 · Watch on YouTube ↗
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