From Java Advent to Legionella: Standards, Specs, and LLMs

discussion about the Java Advent calendar 2025, running AI inference in the enterprise with Java versus python, why inference needs a mature ecosystem, the confusion between machine learning, inference and LLMs, HTTP clients for remote models, TornadoVM for local model acceleration, avoiding premature optimization for LLM-generated code, grounding LLMs against normative Java and Jakarta EE specifications, the separation between API and SPI to eliminate hallucinations, Boundary Control Entity (BCE) structure with self-contained packages for scalable LLM code generation, maximal cohesion and minimal coupling, standards as an effective technique for LLM code generation, MDN web components and custom elements for dependency-free front-ends, reducing context and inference cost with short prompts, AIRails skills site, agents and skills across Copilot and other tools, Eclipse Collections, WebAssembly for Java with Chicory and TornadoVM, pattern matching, Java in industrial and IoT systems at ASML, Legionella water-temperature monitoring with wireless sensors, Apache IoTDB and Apache NiFi, migrating Java Advent to Roq static site generator

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