Building Smart Applications with Agentic AI for JVM developers (Java/Kotlin)

1 January, 2026Hilversum, The Netherlands

2 days
In Person

In this training, you’ll learn the essentials of generative AI and apply them hands-on. From semantic search and RAG to MCP and multi-agent workflows, you’ll build real-world agentic applications using state-of-the-art frameworks like  Spring-AI and LangChain4j that bring next-generation intelligence into your JVM projects.

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Any questions? 

Melchior will gladly help you further with any personal or in-company needs you might have.

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Duration

2 days

Time

09:00 – 17:00 (GMT +1:00)

Language

Nederlands

Lunch

Included

Certification

No

Level

Professional

What will you learn?

In this GenAI for Kotlin Developers training, you’ll unlock the skills to supercharge your JVM applications with AI. 🚀 You’ll not only understand the core principles of generative AI, but also get hands-on experience turning them into real solutions. By the end, you’ll know how to seamlessly integrate AI features into your apps or build powerful agentic systems from scratch using frameworks like LangChain4j and Spring-AI.

Key takeaways

  1. Build intelligent search experiences → Implement semantic search with embeddings and vector databases, covering document processing, data ingestion, and retrieval patterns that enhance enterprise applications.
  2. Master LLM interaction patterns → Apply prompt engineering, generate structured outputs, stream responses, and design Retrieval-Augmented Generation (RAG) systems for real-world use cases.
  3. Design multi-agent AI workflows → Orchestrate complex agentic systems with conditional logic, parallel execution, and monitoring to drive intelligent automation of business processes.
  4. Leverage the Model Context Protocol (MCP) → Learn how create extensible AI applications that interact with external tools and services, enabling seamless integration with UIs like Claude, ChatGPT, or your own LLM-powered apps.

Program

This 2day training covers multiple subjects, which are elaborated more in Overview. This includes AI Fundamentals and tool integration.

Understanding the AI landscape from a backend perspective: APIs vs embedded models, cloud vs on-premise deployment options

Who is it for?

This course is for JVM Developers (Java, Kotlin, Scalal etc.) who want to master building applications with Agentic AI.

Requirements

Basic Java or Kotlin knowledge

Experience with enterprise application development  

Basic Spring Boot knowledge helpful, yet not required

Why should I follow this training?

Master core AI concepts 

Build a strong foundation in generative AI by understanding core concepts like embeddings and semantic search, LLM interaction, tool-calling, and multi-agent systems — and turn them into practical solutions.

Build agentic applications 

Gain hands-on experience with semantic search, RAG, tools, (multi-)agent workflows, and MCP using AI stacks for the JVM like langchain4j, spring-AI, and more.

Future-Proof Your Skills

Stay ahead with the next-generation AI patterns every JVM developer will soon rely on.

What else
should I know?

The following subjects will be treated in-depth, with frequent live-coding samples, hands-on, and group exercises:
– Introduction to AI Fundamentals for Backend Engineers
– Semantic Search with Embeddings and Vector Databases
– LLM Integration and Enterprise RAG Implementation
– Model Context Protocol (MCP) and Tool Integration
– Agentic AI and Multi-Agent Workflows

After registration for this training, you will receive a confirmation email with practical information. A week before the training, we will ask you about any dietary requirements.

See you soon!

Course information

Hands-on practice with your own codebase.

Mix of live demos, interactive labs, and peer collaboration.

Lunch and snacks are included on the first day, refreshments will be provided on the second day.

Travel and accommodation expenses are not covered.    

Meet the trainers

Urs Peter

Urs Peter is a well-known Kotlin trainer and thought leader. Learn more!

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