Backend | Java | Quarkus | AI | Career
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
Quarkus 3.35 ships three optimizations that, stacked together, change the cold-start budget for serverless workloads on Java: build-time JAR tree-shaking, Profile-Guided Optimization for native builds, and Semeru AOT support. Each one targets a different layer. Tree-shaking cuts the classes you ship. PGO improves native code quality. Semeru AOT reduces JVM startup time for teams that … 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
Recently, I sat in on a talk at StartSe AI Festival 2026 that stayed with me for days. On stage was Isabella Piratininga, iFood’s Director of Technology and Innovation, and the subject was building agentic products at scale, told through the case of Ailo, iFood’s conversational assistant. Let me be upfront from the start: this … Read more