Backend | Java | Quarkus | AI | Career
The release notes for Quarkus 3.37.0.CR1 read like a busy week. A wave of entries adds an “AI skill” to specific extensions, including quarkus-quartz, quarkus-hibernate-reactive, quarkus-redis-cache, and quarkus-security-jpa. One line introduces the ability to get response metadata in a streamed response. One enables Jackson reflection-free serializers by default. Two of these lines, read slowly, change … Read more
The LangChain4j 1.16.0 release notes carry a line that should make anyone running a multi-agent system on the JVM stop scrolling: Introduce Blackboard agentic pattern. Until now, when you wanted agents to coordinate in LangChain4j, you reached for one of the orchestration shapes the library already gave you through AgenticServices: a sequence, a parallel fan-out … Read more
Recently there was a decision in the Java world that left a lot of people unhappy. The OpenJDK maintainers decided they will not accept contributions of AI-generated code. Before we react to it, let’s understand what’s actually going on. When you work on an open source project at the scale of Java, the companies behind … Read more
A multi-step agentic workflow is a stateful process. One agent validates an order, another waits on a human decision, a third finalizes it; each step reads and writes shared state, and the whole run can last seconds, minutes, or days. Anything that runs that long eventually gets interrupted. A deploy rolls the pods. The node … Read more
JobRunr shipped ClawRunr, an open-source Java AI agent that runs on your own hardware and executes scheduled, recurring, and one-off background tasks. The part worth an architect’s attention is where the agent lives: inside the same runtime that already runs those jobs. That placement is the whole story. Most “AI agent for the JVM” pitches … Read more