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All Features in Java 26 - Inside Java Newscast #102

By Nicolai Parlog on December 4, 2025

Java 26, or rather JDK 26, enters rampdown phase 1 today, which sets its feature set in stone. With added HTTP/3 support, performance and AOT improvements, new command-line flags to manage final field mutation, and a steady progression of previews, it moves Java forward.

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So Long and Thanks for All the Applets

By Phil Race on December 3, 2025

Java 26 will be the first Java version to ship without the Applet API - 10 years after its deprecation has it been removed by JEP 504.

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JEP targeted to JDK 26: 529: Vector API (11th Incubator)

By Xueming Shen on December 2, 2025

The following JEP is targeted to JDK 26: 529: Vector API (Eleventh Incubator)

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Agent Orchestration with LangChain4J

By Lize Raes on December 1, 2025

Langchain4j is a library that enables developers to easily integrate language models and AI workflows into Java applications, gaining traction within the Java and enterprise AI communities. With the langchain4j-agentic module, you can combine AI (and non-AI) agents into powerful but controlled workflows. In this session, Lize explores the core patterns: sequential, looping, conditional, and parallel, plus the supervisor pattern where agents decide for themselves which tasks to run. She also covers human validation strategies that keep your agents in check. Compound agents wrap entire workflows into a single building block, while AgenticScope provides control over context and a clear view of the call chain. Through playful demos, this presentation shows agent systems that scale from small tasks to complex automation. Whether you are just curious about AI or ready to experiment in your own codebase, you grasp what is possible today, how to keep it under control, and how Java developers shape the next rise of the agents.

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Garbage Collection in Java: Choosing the Correct Collector

By Stefan Johansson on November 29, 2025

Garbage collection (GC) is a type of automatic memory management and a key feature of the Java platform. It allows developers to focus on their application logic rather than low-level memory management issues. The Java platform implements multiple garbage collection algorithms, making it suitable for handling all kinds of workloads. The default collector, G1, is often a great choice, but depending on your use case, another GC might provide even better performance. This video explores: the basics of garbage collection, why there are multiple collectors, key characteristics of G1 and ZGC and the performance differences between collectors and JDK releases.

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Help, My Java Object Vanished (and the GC is Not at Fault)

By Paul Hubner on November 28, 2025

This post provides an insight into Project Valhalla development, while offering insights into the inner workings of HotSpot. It also pragmatically demonstrates how JVM flags can be used to help you, and shares some lessons learned when debugging HotSpot.

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JEP targeted to JDK 26: 526: Lazy Constants (Second Preview)

By Per-Ake Minborg, Maurizio Cimadamore on November 27, 2025

The following JEP is targeted to JDK 26: 526: Lazy Constants (Second Preview)

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Quality Outreach Heads-up - JDK 26: HttpClient Supports TLS Named Groups & Signature Schemes

By Ana-Maria Mihalceanu on November 26, 2025

This Heads-Up is part of the regular communication sent to the projects involved; it covers how HttpClient supports TLS signature schemes and named groups configured on SSLParameters.

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ONNX Based Generative AI LLMs in Java with Project Babylon

By Adam Sotona on November 25, 2025

The Open Neural Network Exchange (ONNX) serves as a universal format for representing machine learning models, facilitating their deployment across diverse platforms. Traditionally, Large Language Models (LLMs) are developed in Python using frameworks like PyTorch, TensorFlow, or scikit-learn, and then exported to ONNX for execution. In this presentation, we demonstrate how Java, a language not traditionally associated with AI modeling, can be utilized to produce ONNX models. We also explore the concept of ONNX-based Generative AI LLMs in Java, leveraging Project Babylon's code reflection capabilities. The presentation showcases a practical Java example of an LLM, detailing its transformation into the ONNX format and subsequent execution.

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JEP targeted to JDK 26: 525: Structured Concurrency (6th Preview)

By Alan Bateman, Viktor Klang, Ron Pressler on November 24, 2025

The following JEP is targeted to JDK 26: 525: Structured Concurrency (Sixth Preview)

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