Backend | Java | Quarkus | AI | Career
Eight configuration mechanisms exist for agentic coding tools. A team of researchers went looking for them in 2,853 GitHub repositories, and what came back is one mechanism carrying almost all the weight. The paper is Harness Engineering for Agentic AI Coding Tools: An Exploratory Study. It builds on work published in AIware 2026. The stated … Read more
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