AI

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

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

There is a tempting way to read the arrival of the Model Context Protocol Java SDK: as one more client library to bolt onto a service. Add the dependency, expose your existing services as tools, point an LLM at it, ship. Glue code. That framing is doing real damage to how Java teams approach LLM … Read more