Conference Sessions
85% Leaner: Cutting the Hidden Cost of AI Agents
Speakers:
As organizations move AI agents into production, they encounter an unexpected bottleneck: token overhead and tool discovery latency. Standard Model …
Agentic Java Development with Eclipse Theia AI: One mvn test at a Time
Speakers:
Developer tools are undergoing a major transformation with the integration of AI coding agents. Eclipse Theia AI provides an open, vendor-neutral …
Black Friday Meltdown: A Java Production War Game
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A gamified 120-minute hands-on workshop where participants step into the shoes of a production support engineering team during a high-stakes Black …
Building MCP Applications with Spring AI
Speakers:
AI applications are evolving beyond simple text chats to interact with real tools, APIs, and external systems. This hands-on workshop teaches Java …
Building Smarter Enterprise AI Applications in Java: Agentic Patterns
Spring AI makes it straightforward to connect an LLM to a Java application. But building a truly useful AI system requires moving beyond simple …
CausaAI: Java Root Cause Analysis with Agentic AI
When a Java application fails in production, finding the root cause is only half the battle. The harder question is: where in the code should we fix …
Demystifying Primitives in Patterns from a Java Programmer's Perspective
Pattern matching in Java has evolved rapidly from instanceof patterns to record patterns and switch expressions. With recent Java releases, support …
Experimenting in Modern Java for Data Science and AI
For years, developers associated Java primarily with heavyweight enterprise applications and multi-module builds. Today, modern Java is remarkably …
How AI Coding Agents Actually Work?
AI coding agents can inspect a repository, edit multiple files, run builds, diagnose failures, and revise their own changes. Yet the language model at …
Project Valhalla: Value Objects, Identity, and Java’s Future
Java developers frequently model data using standard objects, even when that data has no meaningful identity. Project Valhalla bridges the historical …
Resilient AI Agents in Java: A Production Framework for When Reasoning Isn't Enough
AI agents fail in production in ways traditional services don’t: non-deterministic outputs, cascading tool failures, context window exhaustion, …
Running LLMs Natively on the JVM
Every Java shop that adds an LLM feature seems to inherit a second runtime along with it — a Python sidecar running vLLM or TGI, its own deploy …
System Models, JEV — What is it?
As AI systems increasingly participate in core business workflows, a fundamental question emerges: how should humans and intelligent systems …
The hidden JVM tax of running AI agents in Java
AI Agents built on the JVM look like microservices from the outside, but behave unlike anything you have operated before. Long-running LLM streams pin …
When AI Writes the Code, Who Verifies the Logic?
What happens when a non-developer uses AI to build a mission-critical financial verification engine, reverse-engineers transaction formats across 22 …