AI agents are moving beyond chatbots into enterprise applications, where they can reason, use tools, access business data, and perform multi-step tasks. For Java developers, deploying an AI agent mean...

Picture a Java developer shipping an AI agent into production. The agent gets a prompt and starts working through a task, 50 steps, each one a call to a model like OpenAI or Anthropic, a database writ...

In the rapidly evolving landscape of cloud computing, the synergy between popular Java frameworks and powerful cloud platforms is reshaping the way developers approach application development. Azur...

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In this episode, Ayan Gupta is joined by Julien Dubois from Microsoft's Java Developer Advocacy team and a core contributor to LangChain4j, who demonstrates how to build intelligent AI applications with Java. Just like a smart coffee mug that changes color when it senses heat, modern applications need adaptive intelligence, and Julien shows you exactly how to add it. This is the first of two sessions focused on building intelligent AI apps. Julien walks you through the fundamentals of integrating LangChain4j with the official OpenAI Java SDK, showing you how to transform a simple Spring Boot application into an AI-powered poem generator. You'll learn why LangChain4j is the framework of choice for Java AI development, its unified interface means you can easily swap between different LLM providers without rewriting your code. Julien demonstrates how to add LangChain4j dependencies using Maven's bill of materials (BOM) for clean dependency management across multiple modules.You'll configure your first chat model using Azure AI Foundry, connecting to GPT-4o Mini through the official OpenAI SDK implementation. Julien explains the three key parameters you need: the base URL, your API key, and the model name. The beauty of LangChain4j shines through as you see how the same ChatModel interface works across any LLM implementation, whether you're using OpenAI, Mistral, Llama, or GitHub Models. Resources: aka.ms/JavaAndAIForBeginners 0:00 - Introduction: Adding Intelligence to Applications 0:46 - What Is LangChain4j and Why Use It? 1:18 - Creating a New Project with start.spring.io 2:12 - Setting Up Maven with Java 24 2:32 - Running the Basic Application 2:52 - Using GitHub Copilot to Add Command Line Runner 3:29 - Testing User Input Without AI 3:47 - Adding LangChain4j to the Project 4:28 - Understanding Maven Bill of Materials 5:17 - Choosing the OpenAI SDK Integration 5:49 - Configuring the Chat Model 6:27 - Connecting to Azure AI Foundry 7:11 - Getting API Keys and Endpoints 8:27 - Setting Model Parameters 8:47 - Creating the Poem Prompt 9:25 - Testing the AI Integration 10:06 - Seeing the Generated Poem 10:30 - Session Recap and Next Steps #LangChain4j #JavaAI #OpenAI #IntelligentApps #SpringBoot #AzureAI #JavaDevelopment #AIIntegration #ChatModels #AIApplications #Java24

This week, I received an interesting task: dusting off a legacy Java application. The application analyzes specific XML files in proprietary format. I know XML doesn't sound sexy to junior developers,...

Work effectively with a freelance java developer by setting clear goals, using smart tools, and building strong communication for project success.

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