Building AI Applications with Spring AI - Fundamentals
Mark Pollack - Broadcom
Whether you’re just getting started with generative AI or catching up after watching from the sidelines, now is the time to build your foundation. This workshop provides a comprehensive, hands-on introduction to building AI applications with Spring AI 2.0. Designed for Spring developers with no prior AI experience, we’ll cover essential AI concepts and show you how to integrate them into your applications using Spring’s familiar programming model. Bring your laptop and a readiness to learn. We’ll supply Spring AI sample code along with the necessary API keys for AI services. By the end of the day, you’ll have the skills to add generative AI features to your Spring apps.
Key topics covered
Foundations
- Introduction to Generative AI Models
- Prompt Engineering Techniques & Best Practices
- Spring AI Overview & Multi-provider Support
Spring AI APIs
- ChatClient & ChatModel
- Prompt Templates & Roles
- Structured Output: Mapping AI Output to POJOs
- Tools & Function Calling
- Embeddings & Vector Stores
- Multimodal: Image & Audio
- Streaming Responses
Advanced Model Capabilities
- Extended Thinking & Reasoning Mode
- Prompt Caching: Up to 90% Cost Reduction
- Citations API: Source Attribution & Verification
Patterns & Advisors
- The Advisor Abstraction
- Prompt Stuffing & Context Enhancement
- Retrieval Augmented Generation (RAG)
- Chat Memory & Conversation State
Model Context Protocol (MCP)
- MCP Servers: STDIO & HTTP Transports
- MCP Clients
- Dynamic Tool Calling
Introduction to Agentic Patterns
- Chain-of-thought Reasoning
- Inner Monologue & Self-reflection
Production Concerns
- Running Local Models with Ollama
- Observability for AI Applications
- Evaluation: How to tell if the AI is doing what you think