Context Engineering for Java Developers

Prompt engineering was only the beginning. Reliable AI applications depend on the context around the prompt: system instructions, memory, retrieved knowledge, tools, and structured output.

In this live-coding session, we'll use Spring AI to build that context deliberately. We'll load the right information at the right time and avoid overwhelming the model. You'll leave with a practical mental model for building AI applications Java can trust.

What You'll Learn

• Why the context around the prompt, not the prompt itself, decides whether an AI feature is reliable
• System instructions that set the rules for every request
• Chat memory, and how much of it the model actually needs
• Retrieval augmented generation (RAG) that loads the right knowledge at the right time
• Tools that let the model call your Java code
• Structured output that turns responses into Java records
• How to keep the context window focused instead of stuffed