The Java community thrives on sharing knowledge and experiences. Most content is in English, which works well for many developers. However, there's something special about discussing complex topics in your native language. The nuances. The humor. The ability to express yourself freely without translating your thoughts first.

That's why we created JCast, a podcast for the Dutch-speaking developer community. Moreover, today we're excited to launch Season 2!

Season 2 Starts with Frank Delporte

For our second season opener, we sat down with Frank Delporte. He's well-known in the Java community as a Java Champion. Additionally, he's a Java Developer, Technical Writer at Azul, Blogger, and Author of "Getting started with Java on Raspberry Pi". Furthermore, he's a Pi4J Contributor.

In this episode, Frank shares his unique journey. From film school to Java Champion. His work on Pi4J. Making Java accessible on embedded devices like the Raspberry Pi. And his passion for documentation and CoderDojo.

Ultimately, it's a conversation about code as communication. About bridging hardware and software. And how documentation is as important as the code itself.

Listen now at jcast.dev

What is JCast?

JCast is a podcast about IT, dev life, and soft skills. As we like to say: "gezonde meningsverschillen" (healthy disagreements).

Hosted by three developers from Belgium: Oumaima, Viktor, and Maarten. Together, we sit down with guests from the Dutch-speaking tech community. Our goal? To explore what it really means to work in software development.

We describe ourselves as "drie developers met een liefde voor code en een gezonde dosis chaos" (three developers with a love for code and a healthy dose of chaos). That energy defines our conversations.

Meet the Hosts

Oumaima Zerouali is a developer who loves clarity and challenges. She's passionate about the 'why' behind systems and people. Backend, frontend, or cloud. She wants to understand it, master it, and make it better.

Viktor Van Steenweghen is a software engineer who lives for clean code and automation. He's a fan of AI tools and nerdy discussions. Always curious about new shortcuts.

Maarten Casteels is a pragmatic tech lead with a sharp eye for detail. He has a soft spot for good teamwork. He loves clean code, clear communication, and a bit of chaos from time to time.

What We Talk About

Our episodes explore various topics:

• Development & Technology: Modern frameworks. Cloud architectures. The evolving tech landscape.
• Soft Skills: Communication. Team dynamics. Career growth.
• Developer Life: The realities of working as a developer. Including the challenges we don't always talk about.
• AI & Innovation: Practical applications. Tools that actually work.
• Community & Open Source: Learning from contributors and champions in the Java ecosystem.

Why We Started JCast

A year ago, we had an idea. What if Dutch-speaking developers had a podcast in their own language? Not because English is hard. But because sometimes you just want to listen without translating in your head.

After 12 episodes in Season 1, the response has been great. People listen during their commute. While coding. Or during lunch.

More Than Just Code

What sets JCast apart is our holistic approach. We don't just focus on frameworks and algorithms. Instead, we explore the human side of development.

Communication. Understanding people. Navigating team dynamics. And yes, those "gezonde meningsverschillen" that make collaboration both challenging and rewarding.

Being a good developer isn't just about writing perfect code. It's about the whole picture.

From Season 1 to Season 2

Season 1 brought us 12 episodes of honest conversations. Capacity planning. Developer hobbies. New Year's resolutions. The real challenges of modern development.

Season 2 continues that journey with even more inspiring guests. We're kicking off with Frank Delporte. Java on Raspberry Pi. His path to Java Champion. Why documentation matters as much as code.

More exciting conversations are coming. We can't wait to share them with you.

Where to Listen

JCast is available on all major podcast platforms:

• Website: jcast.dev
• Spotify: JCast on Spotify
• Apple Podcasts, Amazon Music, Deezer, and other platforms

Start with Season 2, Episode 1 featuring Frank Delporte. Available now!

Final Thoughts

JCast is our contribution to the Dutch-speaking developer community. A place where technical excellence meets honest conversation. Where we can discuss both the 'how' and the 'why' of what we do.

Season 2 is here. And we're excited about the conversations ahead.

The post Introducing JCast: Conversations About Java and Developer Life in Dutch appeared first on foojay.

In this episode of the Foojay Podcast, we're bringing you something special: a full batch of hallway-track conversations recorded live at VoxxedDays Amsterdam.

Fifteen guests, one conference, and one theme that kept coming back, whether we planned it or not: Java has grown up quietly, steadily, and in ways that still surprise people who haven't looked lately. We talked about migrating between versions, new features in the latest Java releases, authorization done right, AI-assisted coding, cryptography, containers, open-source contributions, GDPR data experiments, and, yes, the things people hate about Java but secretly love.

I spoke with Ko Turk, who organized this very conference, Johannes Bechberger, Lutske de Leeuw, Aicha Laafia, Marit van Dijk, Adele Carpenter, Patrick Baumgartner, Sohan Maheshwar, Jeroen Egelmeers, Erwin Manders, Alexander Shopov, Maarten Verburg, Arjan Tijms, Joost Kaan, and Stephan Janssen.

That's a lot of people. That's a lot of opinions. And somehow, they mostly agree: update your JDK, read your code, and please talk to your actual users.

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• Spotify
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Content

00:00 Introduction

00:30 Ko Turk

• https://www.linkedin.com/in/ko-turk-b271b929/
• Organizer of VoxxedDays Amsterdam
• Migrating between Java versions

02:25 Johannes Bechberger

• https://www.linkedin.com/in/johannes-bechberger/
• Java is boring, and that's why it's brilliant
• Java 26 test it, but not in production
• JFR improvements in the latest versions

06:28 Lutske de Leeuw

• https://www.linkedin.com/in/lutske/
• Volunteer at the conference
• Java is boring, and that's why it's brilliant
• Java 5 till 26 evolutions

10:35 Aicha Laafia

• https://www.linkedin.com/in/aicha-laafia-0266a6126/
• Lambda stream gatherers in Java 25
• Simpler and more fun code
• Update your JDK!

16:16 Marit van Dijk

• https://www.linkedin.com/in/maritvandijk/
• Fun in coding, write Java the playful way
• Java evolutions and how writing code has evolved
• Importance of code reading with AI-assisted coding

22:04 Adele Carpenter

• https://www.linkedin.com/in/adele-carpenter-a988623a/
• The things I hate about Java, but actually love it

27:37 Patrick Baumgartner

• https://www.linkedin.com/in/patbaumgartner/
• Organizing VoxxedDays Zurich
• Spring Boot optimization
• Using Buildpacks to create better containers

35:02 Sohan Maheshwar

• https://www.linkedin.com/in/sohanmaheshwar/
• Authorization, the good way
• JWT is a bad idea

38:34 Jeroen Egelmeers

• https://www.linkedin.com/in/jegelmeers/
• https://craftingaiprompts.org/documentation/se-framework/craft-framework
• AI, prompt engineering, agentic programming
• The CRAFT Framework: Orchestrating Agentic Flow
• The importance of interacting with your end-users

43:32 Erwin Manders

• https://www.linkedin.com/in/erwinman/
• Cryptography, digital signatures, and securing data and messages
• Comparing Kotlin and Java

45:12 Alexander Shopov

• https://www.linkedin.com/in/alshopov/
• Developer at Uber
• Comparing different languages: Java, Python, Go
• How Java is modernizing by learning from other languages

49:18 Maarten Verburg

• https://www.linkedin.com/in/maartenverburg/
• Using your own GDPR data for fun experiments
• Comparing early Java with the current status
• Java Streams the most important change

52:35 Arjan Tijms

• https://www.linkedin.com/in/arjantijms/
• https://omnifish.ee/
• Jakarta Faces, Security, Authentication and Authorization, EE,...
• Jakarta specs are used in Spring
• How Java evolved and is still evolving
• How can you contribute to opensource

59:55 Joost Kaan

• https://www.linkedin.com/in/joost-kaan/
• What you can learn at a conference, besides the expected language-related talks
• AI influences on the developer work
• Contributing to the Java community, AI user group

01:03:52 Stephan Janssen

• https://www.linkedin.com/in/stephanjanssen/
• https://geniebuilder.ai/
• The importance of the "Hallway Track" where you can chat with like-minded people
• Using AI-assisted spec-driven coding
• Talking to your end-user becomes more important than ever

01:09:00 Conclusion

The post Foojay Podcast #93: Update Your JDK, Read More Code, and Talk to Your Users: Interviews From VoxxedDays Amsterdam appeared first on foojay.

Steve Poole | With contributions from James Fredley, Apache Grails PMC Chair

For a technology that many people filed under “legacy,” Grails has been unusually active. While much of the industry’s attention has drifted toward newer frameworks and shinier stacks, something more deliberate has been happening in the background.

Grails has been moving into the Apache Software Foundation (ASF), modernising and positioning itself for the next chapter.
If you have not looked at Grails recently, your mental model is likely several years out of date. And that, in many ways, is exactly the problem.

The technology we stop seeing

Software ecosystems rarely end with a bang; most of the time, they simply slip out of focus. Conference agendas move on, blog coverage thins out, and new frameworks capture the narrative. Eventually, we collectively “agree” that a technology is “basically done”.

Except in enterprise environments, that is often not true at all. There are still Grails applications in production, processing transactions and serving customers. But while the systems remain, the organisational spotlight has shifted.

There is a significant gap between what gets hype and what actually runs the web.

According to W3Techs, PHP powers roughly 71.8% of all websites whose server-side language is known. Between 40% and 60% of the web runs on WordPress alone.

JavaScript, for all its conference-circuit dominance, accounts for under 6% on the server side. The technologies that quietly keep the internet running and the ones that dominate the narrative are often not the same technologies at all.

Why the Apache move matters

The transition of Grails into the ASF is not merely administrative tidying. Moving under the ASF umbrella is one of the clearest signals an open-source project can send about its long-term intent.

ASF provides a neutral home, predictable release discipline, and a contributor model that reduces perceived vendor risk.

For Grails, this matters because mature platforms live or die on trust signals. The ASF move changes the risk conversation for organisations evaluating whether Grails still has a place on their servers.

Twenty years of changing hands

The context makes the move even more significant. Grails was primarily led by single organisations for most of its 20-year history: G2One from 2005 to 2008, then SpringSource through 2015, Object Computing through 2021, and the Grails Foundation/Unity Foundation through 2025.

Each transition introduced uncertainty about the project’s direction and sustainability.

The ASF model is designed to break that pattern, replacing single-organisation dependency with volunteer-driven governance, vendor neutrality, and the structured transparency of the Apache Way.

Eighteen months of migration

In October 2025, Grails officially graduated from incubation to become a Top-Level Project at the ASF, following a board vote in September.

That sounds like a single event. It wasn’t. The migration was an 18-month process that began in late spring 2024 with a volunteer team assessing project readiness and submitting an incubation proposal.

What followed was a substantial modernisation effort: merging repositories into a mono-repo, overhauling the build system and dependency management, upgrading Maven coordinates, and issuing releases under ASF governance. The first ASF release (Milestone 4) shipped in June 2025, with the 7.0.0 General Availability release arriving in October.

One hundred repositories become nine

The scale of the repository consolidation tells its own story. Grails originally had around 100 Git repositories, of which 43 were slated for ASF migration. By the time the move was complete, those had been consolidated to 18, with only 9 still in active use.

That is a lot of plumbing.

The mono-repo approach accelerated compliance with ASF policy but required integrating separate build systems and release processes across hundreds of commits.

Over 2,000 commits went into the grails-core mono-repo alone, and build times for a release dropped from over three weeks to approximately 30 minutes.

Read that again. Three weeks to thirty minutes.

Beyond the code: licensing and compliance

The code was only part of it. The team also had to meet ASF security and licensing requirements. Reproducible, verifiable builds were implemented (requiring upstream contributions to dependencies including Apache Groovy).

Every source file was reviewed for licence headers, and 327 separate artefacts were audited for licensing compliance. The team automated licence review by adopting Software Bill of Materials for every published jar, ensuring ongoing compliance with reduced future effort.

Migrating the fully automated Gradle and GitHub Actions workflows proved to be a novel challenge in its own right; other Gradle-based projects at the ASF are now looking at the result as a reference implementation.

The modernisation you might have missed

A significant amount of careful modernisation has been focused on keeping Grails aligned with the moving baseline of the JVM and the Spring ecosystem.

This is not cosmetic: dependencies have been pulled forward, and compatibility with newer Java runtimes has been tightened.

What Grails 7 actually ships

Grails 7.0.0 shipped in October 2025 as the first stable release under ASF stewardship. It brings major dependency upgrades including Java 17+ support (through to Java 25), Groovy 4, Spring Boot 3.5, Spring Framework 6.2, and Jakarta EE 10.

Alongside the platform alignment, the release introduced containerised browser testing via Testcontainers and Geb, optional Micronaut integration, SBOM generation for all published binaries, and reproducible builds and artefacts.

The grails-core mono-repo now produces over 325 published jar files across 109 Gradle projects, with local build times between two and ten minutes depending on caching and hardware.

Grails 8 and the release cadence

Grails 8 development started in late November 2025, tracking Spring Boot 4.0 which reached general availability at the end of that month.

The project now follows Spring Boot’s six-month release cadence, with 13 months of support per release. Giving teams predictable timelines to plan around.

The humans behind the reboot

Open-source projects do not evolve by inertia. They move forward because a relatively small number of people decide the work is worth doing.

One of the challenges Grails faces today is not a lack of activity but a lack of visible narrative.

Much of the effort is concentrated in a tight group of committed maintainers. From the outside, that can appear to be silence even when meaningful progress is underway.

To make that work more visible, I spoke with James Fredley, the Apache Grails PMC Chair, about where the project stands and where it is heading.

What motivated the move to the Apache Software Foundation?

There were real questions about Grails’ future, and they were understandable.

The concerns crept in during the 4.x through 6.x era, when the project moved through several organisations and its direction felt uncertain. For most of its 20-year history, Grails was primarily led by a single organisation at any given time, with limited community contributions or input.

The move to the ASF was about addressing that directly: shifting from single-organisation dependency to a volunteer-driven, vendor-neutral model. The ASF’s structure: the Project Management Committee, mailing lists, consensus-based voting, the incubation process, gives people confidence that the project is sustainable, not dependent on any one company’s priorities.

From inside the project, what kind of technical work has been happening?

The scale of it probably surprises people. Thousands of hours of volunteer time have gone into modernising the 7.x line and building toward 8.x.

We consolidated from around 100 repositories down to 18 (with 9 active), rewrote the build and release pipeline, achieved reproducible and verifiable builds, implemented SBOM generation, and ensured licensing compliance across hundreds of artefacts.

Grails 7 now produces over 325 published jar files across 109 Gradle projects, with local build times between two and ten minutes. The release process itself went from a three-week ordeal to about 30 minutes.

Migrating our fully automated Gradle and GitHub Actions workflows to the ASF was a novel challenge, but grails-core can now serve as a model for other Gradle-based projects joining the Foundation.

What people also need to understand is that a Grails application is a Spring Boot application.

With roughly 85–90% of Java applications running on Spring Boot,Grails is not some exotic outlier: it is extra developer-productivity layers on top of what everyone in the Java ecosystem already uses.

What do you hope the ASF transition unlocks?

Broader adoption and broader contribution. The ASF gives us credibility with enterprise decision-makers who need to know a framework will still be around in five or ten years.

But it also lowers the barrier for new contributors. The governance is transparent, the processes are well-documented, and the project is genuinely welcoming.

Grails now follows Spring Boot’s release cadence: a six-month cycle with 13 months of support, which gives teams predictable timelines to plan around.

What misconception about Grails would you most like to correct?

That it’s a legacy technology for legacy teams.

Grails is still the most productive way to build a web application in the Java ecosystem, and that should be a draw for newer engineers and greenfield projects, not just established estates.

The convention-over-configuration approach means less boilerplate, sensible defaults, and a gentle learning curve.

It is a “framework of frameworks,” built on Spring Boot, Spring Framework, Jakarta EE, and Hibernate.

If you know those, you already know a significant part of Grails.

Where Grails realistically sits in 2026

Grails is not trying to out-Spring Boot Spring Boot. Where it continues to make sense is in environments that value convention-heavy productivity and rapid delivery, particularly where there is already meaningful investment in the Groovy ecosystem.

For teams with established Grails estates, the question isn’t “does it work?” but “is it still safe to stay?”

The ASF graduation, the release of Grails 7 (supporting Java 17 through 25), and the active development of Grails 8 tracking Spring Boot 4 are designed to lower the perceived risk of that decision. But that safety is contingent on moving forward.

For teams evaluating new projects, the productivity argument deserves a fresh hearing. As Fredley puts it, Grails is extra developer-productivity layers on top of what 85–90% of the Java ecosystem already uses. That framing: not “legacy framework” but “productivity accelerator built on Spring Boot”, is a different proposition than the one most people have filed away in their mental models.

The hard work that keeps software alive

Software rarely dies because of a single technical flaw; it fades because attention moves somewhere else.
What the current maintainers are doing is the careful, methodical work required to keep a mature framework viable in a fast-moving ecosystem.

In an industry that celebrates only the new, that kind of work, and the difficult EOL conversations it requires, is easy to overlook.

It probably should not be.

Of course, none of this helps the teams still running Grails 3 or 4 on their servers. For them, the dependency cliff is already here. In part two, I want to look at what that cliff actually looks like and what the options are.

Resources

• Apache Grails Support Schedule
• HeroDevs Grails EOL Support
• Spring Boot End of Life Dates
• HeroDevs Spring Boot EOL Support
• ASF Graduation Announcement
• Grails 7.0.0 Release Announcement
• Introduction to Apache Grails 7 (Community Over Code NA 2025, James Fredley
• Migrating a 20 Year Old Project to the ASF (Community Over Code NA 2025, James Fredley)

Author’s note:

In the interest of transparency, I work for HeroDevs, a company that provides extended support for end-of-life open-source components. If you are currently assessing the support posture of older Grails estates, it is worth understanding the continuity support options available in the Java ecosystem. The landscape has evolved significantly in the past few years.

The post Grails Isn’t Done Yet (Part 1): Inside the ASF Reboot appeared first on foojay.

article: Exclusive: Why are Chinese AI models dominating open-source as Western labs step back?
authors: Dashveenjit Kaur, AI News
date: 2026-02-09
desc.: A shift in what AI models are being used and where the models are being produced.
category: opinion

article: Machines of Loving Grace
authors: Dario Amodei
date: 2024-10-01
desc.: Although the article is older, it remains relevant for any author aiming to sketch a future in which everything with AI goes right. In light of recent developments, which appear to follow a sigmoid curve rather than exponential growth (marked by stagnation, with current models reaching a point where another breakthrough is required), the trajectory looks more measured than initially anticipated. Although the author discusses multiple risks (grandiosity, market forces, propaganda, sci-fi-like expectations, etc.), he also highlights the bright sides and explores areas where current AI may prove genuinely helpful. The question remains whether the current state of affairs can truly guarantee progress, rather than causing damage through non-deterministic outcomes (education, industry, human creativity etc.).
category: opinion

article: The Urgency of Interpretability
authors: Dario Amodai
date: 2025-04-01
desc.: The author describes lessons learned from current AI development and adds multiple valuable thoughts and facts to consider when interacting with AI models. The main point is that progress in the underlying technology is inexorable, driven by forces too powerful to stop, but what matters is the way in which it unfolds. Accepting that the current evolution of LLM-based AI cannot be halted, the author expresses hope that it may still be guided (this fact affect not only entire industry but also human kind thoughs and perception of reality), much like a bus controlled by a steering wheel, and warns of the dangers of ignorance, illustrating this through several concrete examples.
category: opinion

article: From Delegates to Trustees: How Optimizing for Long-Term Interests Shapes Bias and Alignment in LLM
authors: Suyash Fulay, Jocelyn Zhu, Michiel Bakker (MIT)
date: 2025-10-14
desc.: The article addresses the question of 'behavioral cloning', specifically, how accurately LLMs reproduce individuals' expressed preferences. Large language models have demonstrated promising accuracy in predicting survey responses and policy preferences, which has fueled growing interest in their potential to represent human interests across various domains. Drawing on theories of political representation, the article highlights an underexplored design trade-off: whether AI systems should act as delegates, mirroring expressed preferences, or as trustees, acting in users' broader interests. Models may align well with users' short-term preferences while failing to account for their long-term interests. Studies further indicate greater bias in topics where consensus is lacking.
category: research

article: DARE-bench: Evaluating Modeling and Instruction Fidelity of LLMs in Data Science
authors: Fan Shu, Yite Wang, Ruofan Wu, Boyi Liu, Zhewei Yao, Yuxiong He, Feng Yan
date: 2026-02-27
desc.: The article addresses the challenge posed by fast-growing demand for Large Language Models (LLMs) to tackle complex, multi-step data science tasks, which has created an urgent need for accurate benchmarking. Two major gaps are identified in existing benchmarks: (i) the lack of standardized, process-aware evaluation that captures instruction adherence and process fidelity, and (ii) the scarcity of accurately labeled training data. While highlighting that even capable models (Anthropic, OpenAI, etc.) may struggle in performance, the article introduces the DARE-bench benchmark alongside supervised fine-tuning as approaches that may improve outcomes in specific applications. Although the results appear promising, they retain considerable potential for further improvement, as accuracy is not yet guaranteed.
category: research

article: Do LLMs Benefit From Their Own Words?
authors: Jenny Y. Huang, Leshem Choshen, Ramon Astudillo, Tamara Broderick, Jacob Andreas (MIT, IBM Research)
date: 2026-02-27
desc.: The article aims to answer the question of whether preserving past assistant responses is more beneficial than harmful. The study uses in-the-wild, multi-turn conversations and compares standard (full-context) prompting with a user-turn-only prompting approach that omits all previous assistant responses, evaluated across three open reasoning models and one state-of-the-art model. Surprisingly, omitting past assistant responses does not negatively affect response quality in a large fraction of turns and may also reduce token length. The article concludes with a discussion of findings and directions for future research.
category: research

article: SafeGen-LLM: Enhancing Safety Generalization in Task Planning for Robotic Systems
authors: Jialiang Fan, Weizhe Xu, Mengyu Liu, Oleg Sokolsky, Insup Lee, Fangxin Kong
date: 2026-02-27
desc.: Safety-critical task planning in robotic systems remains a significant challenge: classical planners suffer from poor scalability, reinforcement learning (RL)-based methods generalize poorly, and base large language models (LLMs) cannot guarantee safety. To address this gap, the article proposes SafeGen-LLM, a safety-generalizable large language model framework. As part of this contribution, a multi-domain Planning Domain Definition Language 3 (PDDL3) benchmark with explicit safety constraints is introduced, along with Supervised Fine-Tuning (SFT) on those constraints. Although the results appear optimistic, with minimal safety violations observed across tested domains, the approach still requires further research in more complex robotic settings.
category: research

article: LemmaBench: A Live, Research-Level Benchmark to Evaluate LLM Capabilities in Mathematics
authors: Antoine Peyronnet, Fabian Gloeckle, Amaury Hayat
date: 2026-02-27
desc.: Existing benchmarks largely rely on static, hand-curated sets of contest or textbook-style problems as proxies for mathematical research. The article introduces a novel approach leveraging state-of-the-art models (GPT-5, Gemini 2.5, Gemini 3, Claude Opus 4.5, and DeepSeek-R) by extracting lemmas from arXiv and updating them dynamically. This results in a benchmark that can be refreshed regularly with new problems drawn directly from current mathematical research, while previous instances can be used for training without compromising future evaluations. This approach achieves 10–15% accuracy in theorem proving and opens a new frontier for future research. Although the process may appear fully automated, a human in the loop, such as the article's author or reviewer, remains critically necessary to produce high-quality inputs and to effectively use LLM models.The results also indicate that it is considerably easier for a model to validate an existing proof than to produce one.
category: research

article: Task Complexity Matters: An Empirical Study of Reasoning in LLMs for Sentiment Analysis
authors: Donghao Huang, Zhaoxia Wang
date: 2026-02-27
desc.: It is a well-established narrative that reasoning in large language models (LLMs) universally improves performance across language tasks. This article aims to test that claim through a comprehensive evaluation of 504 configurations across seven models, considering different reasoning architectures such as adaptive, conditional, and reinforcement-based approaches. The findings reveal that the effectiveness of reasoning is strongly task-dependent and degrades for simpler tasks. The article provides quantitative findings alongside error analysis and outlines directions for future research.
category: research

article: Benchmarking LLM Summaries of Multimodal Clinical Time Series for Remote Monitoring
authors: Aditya Shukla, Yining Yuan, Ben Tamo, Yifei Wang, Micky Nnamdi and others
date: 2026-03-02
desc.: Large language models (LLMs) can generate fluent clinical summaries of remote therapeutic monitoring time series, however, the impact of information bias on clinically significant events, such as sustained abnormalities, remains poorly understood. The article presents the Technology-Integrated Health Management (TIHM) framework to address these questions, introducing a protocol that measures abnormality recall, duration recall, and measurement coverage, while utilizing GPT-4o-mini as a proxy evaluator. Traditional models frequently exhibit near-zero abnormality recall, whereas the vision-based approach achieves the strongest event alignment, with 45.7% abnormality recall and 100% duration recall. These results underscore the need for event-aware evaluation methods in future research to ensure reliable clinical time-series summarization.
category: research

article: Full interview: Anthropic CEO responds to Trump order, Pentagon clash
authors: CBS News
date: 2026-02-28
desc.: Anthropic CEO Dario Amodei sat down with CBS News for an exclusive interview, hours after Defense Secretary Pete Hegseth declared the company a supply chain risk to national security, which restricts military contractors from doing business with the AI giant. Amodei called the move "retaliatory and punitive," and he said Anthropic sought to draw "red lines" in the government's use of its technology because "we believe that crossing those lines is contrary to American values, and we wanted to stand up for American values.". Response of the OpenAI striking a deal with Pentagon causes many questions.
category: youtube

article: Scary Agent Skills: Hidden Unicode Instructions in Skills ...And How To Catch Them
authors: Embrace The Red
date: 2026-02-11
desc.: Skills introduce common threats such as prompt injection, supply chain attacks, remote code execution (RCE), and data exfiltration, among others. This post discusses the fundamentals, highlights the most straightforward prompt injection vector, and demonstrates how a real Skill from OpenAI can be back-doored using invisible Unicode Tag code-points, a technique that certain models, including Gemini, Claude, and Grok, are known to interpret as instructions. From a security perspective, Skills present serious concerns, as they represent a typical supply chain risk with limited governance or security controls. The author identified that some Skills instruct the AI to embed API tokens directly in curl requests and similar constructs , a poor design practice. This means that credentials are passed through the LLM, making them susceptible to leakage and leaving them vulnerable to being overwritten by an attacker via indirect prompt injection.
category: tutorial

The post JC-AI Newsletter #14 appeared first on foojay.

While significant activity characterizes the AI field, many unresolved research, design, and implementation challenges continue to impact progress. Future advancement depends heavily on understanding the nature of these challenges to approach probabilistic problems from the appropriate directions. This JC-AI newsletter features insightful interviews with key figures in the field, enabling readers to ask the right questions and compare visions of an 'uncertain future' against current capabilities to maintain a grounded perspective.

article: Deep Researcher with Sequential Plan Reflection and Candidates Crossover (Deep Researcher Reflect Evolve)
authors: Saurav Prateek
date: 2026-01-28
desc.: This paper introduces Deep Researcher, a novel architecture that shifts the paradigm from latency-optimized parallel scaling to an accuracy-driven sequential refinement model. Within the development of Deep Research Agents (DRAs), two primary paradigms are considered, Parallel Scaling and Sequential Refinement. The Deep Researcher agent achieved an overall score of 46.21 on the Research Bench, demonstrating superior performance compared to existing agents, including Claude Researcher, Nvidia AIQ Research Assistant, Perplexity Research, Kimi Researcher, and Grok Deep Search. While these improvements are good, the field requires further research to address remaining challenges.
category: research

article: Manipulation in Prediction Markets: An Agent-based Modeling Experiment
authors: Bridget Smart, Ebba Mark, Anne Bastian, Josefina Waugh (University of Oxford)
date: 2026-01-28
desc.: The paper investigates the utilization of agentic systems in the economic field and their impact on prediction. First, the paper evaluates an agent-based model of a prediction market in which bettors with heterogeneous expertise, noisy private information, variable learning rates, and budgets observe the evolution of public opinion on a binary election outcome to inform their betting strategies in the market. The agentic system exhibits stability across experiments. The second area relates to experiments on how "whale" agents, a highly resourced minority with biased information, may distort market prices and for how long. The paper discusses interesting simulation results on how biased information may change the market from a long-term perspective.
category: research

article: Beyond Accuracy: A Cognitive Load Framework for Mapping the Capability Boundaries of Tool-use Agents
authors: Qihao Wang, Yue Hu, Mingzhe Lu, Jiayue Wu, Yanbing Liu, Yuanmin Tang
date: 2026-01-28
desc.: While LLMs' ability to use external tools enables powerful real-world applications, current benchmarks focus on final accuracy rather than revealing the cognitive bottlenecks that limit their true capabilities. This paper presents a framework based on Cognitive Load Theory that aims to decompose tasks into two components: Intrinsic Load and Extraneous Load. The paper discusses performance inconsistencies as cognitive load increases, and demonstrates how the proposed framework enables the identification of capability boundaries in the examined examples.
category: research

article: Build a Prompt Learning Loop - SallyAnn DeLucia & Fuad Ali, Arize
authors: AI Engineer, Sally Ann Delucia, Fuad Alli (Arize)
date: 2026-01-06
desc.: This talk aims to provide ideas on how it is possible to improve LLM responses by using feedback loops. It's important to view this talk through the lens of current research results regarding the LLM hallucination phenomenon and other factors. The main reason to keep current research results in mind is to avoid ending up in an infinite loop of failure/error.
category: youtube

article: Stanford CS230 | Autumn 2025 | Lecture 8: Agents, Prompts, and RAG
authors: Stanford Online
date: 2025-11-11
desc.: For more information about Stanford’s Artificial Intelligence professional and graduate programs
category: youtube, tutorial

article: Developer Experience in the Age of AI Coding Agents – Max Kanat-Alexander, Capital One
authors: AiEngineer, Max Kanat-Alexander
date: 2025-12-23
desc.: It feels like every two weeks, the world of software engineering is being turned on its head. Are there any principles we can rely on that will continue to hold true, and that can help us prepare for the future, no matter what happens? Max uses research, data, and his 20+ years working in enterprise Developer Experience teams to talk through what we can do now that will prepare us for an agentic future, no matter what that future holds.
category: youtube, opinion

article: Token-Guard: Towards Token-Level Hallucination Control via Self-Checking Decoding
authors: Yifan Zhu, Huiqiang Rong, Haoran Luo
date: 2026-01-29
desc.: Hallucination is a recognized phenomenon in the LLM field that impacts applications such as Retrieval-Augmented Generation (RAG) and Reward Modeling (RM). This paper introduces Token-Guard, a self-checking mechanism designed to identify and control hallucinations at the token level. The experiments demonstrate improvements.
category: research

article: Reward Models Inherit Value Biases from Pretraining
authors: Brian Christian, Jessica A. F. Thompson, Elle Michelle Yang, Vincent Adam, Hannah Rose Kirk and others (University of Oxford, University Pompeu Farba)
date: 2026-01-28
desc.: Despite their importance in LLM alignment, reward models (RMs) remain under-researched. This paper provides evidence that RMs inherit biases from their base models, suggesting that the choice of an open-source model is a reflection of values as much as performance. The paper discusses limitations of experiments and offers avenues for future research.
category: research

article: Professor Geoffrey Hinton - AI and Our Future
authors: City of Hobart, Geoffrey Hinton
date: 2026-01-08
desc.: Professor Geoffrey Hinton, known as the "Godfather of AI", will discuss artificial intelligence - how it works, the risks it poses to our society, and how we might coexist with super-intelligent AI. Ideal for business leaders, creatives, researchers, educators, students and anyone curious about the future of intelligence and society.
category: opinion

article: Your MCP Server is Bad (and you should feel bad) - Jeremiah Lowin, Prefect
authors: AI Engineer, Jeremiah Lowin
date: 2026-01-12
desc.: Too many MCP servers are simply glorified REST wrappers, regurgitating APIs that were designed for SDKs rather than agents. This leads to confused LLMs, wasted tokens, and demonstrably poor performance. If you have ever pointed an MCP generator at an OpenAPI spec and called it a day, this talk is your wake-up call.
category: youtube

article: Frontier Models & AI | Sam Altman, CEO & Co-Founder, OpenAI
authors: Cisco
date: 2026-02-04
desc.: Although Sam Altman, CEO and Co-Founder of @OpenAI, explores ideas about future possibilities and potential developments, he is asked during the interview to align his vision with the current state of research and existing technological capabilities. The interview, however, does not present clear data demonstrating how Codex outperforms alternatives or what 'better' specifically means in this context. The responses to questions may appear to be non-deterministic in nature. The interview relies heavily on thoughts about an "undefined future" that would require a deterministically defined foundation. It is interesting how the interview examined frontier AI models and their implications for economies, institutions, and global systems.
category: opinion

article: How to build secure and scalable remote MCP servers
authors: Den Delimarsky (Microsoft)
date: 2025-07-25
desc.: The tutorial provides insights into how to build a reliable Model Context Protocol (MCP) server, enabling AI agents to connect to external tools. It covers several crucial areas and provides valuable resources and ideas for tackling the challenge.
category: tutorial

The post JC-AI Newsletter #13 appeared first on foojay.

This is the next part in the series of "JavaFX in Action" interviews. Are you working on a fantastic JavaFX application? Let me know, and let's discuss it in the new year!

1. July '24: Pedro Duque Vieira, Daniel Zimmermann, Christopher Schnick, and Robert Ladstätter
2. November '24: Maciej Gorywoda, Ramiro Domínguez Ayub, Christoph Schwentker, Ulas Ergin
3. December '24: Özkan Pakdil, Clément de Tastes, Almas Baim, Steve Hannah, Jago de Vreede
4. March '25: Mike Hearn, Sven Reimers, Chris Newland
5. July '25: Cormac Redmond, Brian Schlining, Gerrit Grunwald, Dirk Lemmermann

Vlad Protsenko: Combining Clojure with JavaFX for Game Development with Defold

Vlad Protsenko is a Senior Developer with proficiency in many JVM-based languages. He worked both in very small and large teams, gaining experience in developing projects of various sizes, from scratch and from legacy codebases. He enjoys full-stack development, writing backend, frontend, and Android applications. He started as a game developer and switched to developing enterprise software, currently mixing both at Defold.

The Cljfx library is a declarative, functional, and extensible wrapper of JavaFX. It’s inspired by the better parts of react and re-frame:

• Like react, it allows to specify only desired layout, and handles all actual changes underneath. Unlike react (and web in general) it does not impose xml-like structure of everything possibly having multiple children, thus it uses maps instead of hiccup for describing layout.
• Like reagent, it allows to specify component descriptions using simple constructs such as data and functions. Unlike reagent, it rejects using multiple stateful reactive atoms for state and instead prefers composing ui in more pure manner.
• Like re-frame, it provides an approach to building large applications using subscriptions and events to separate view from logic. Unlike re-frame, it has no hard-coded global state, and subscriptions work on referentially transparent values instead of ever-changing atoms.
• Like fn-fx, it wraps underlying JavaFX library so developer can describe everything with clojure data. Unlike fn-fx, it is more dynamic, allowing users to use maps and functions instead of macros and deftypes, and has more explicit and extensible lifecycle for components.

More info in this blog post.

Matt Coley: Diving into byte code and JARs with Recaf and JavaFX libraries

Matt Coley got into Java development when he wanted to find out how Minecraft works. Because of his many experiments, he gained a lot of knowledge about Java byte code, how it can be converted back to Java code, and how JARs can hide the real code from the user or contain malicious code. He combines all his knowledge in the Recaf tool and the JavaFX libraries he created.

Recaf is an open-source Java bytecode editor that simplifies the process of editing compiled Java applications. To make things easier, Recaf abstracts away much of the class file format. Challenging tasks such as updating stack frames are done automatically. Along with additional features to help in the process of editing classes, Recaf is the most feature-rich bytecode editor available.

As Recaf wants to provide an IDE similar to IntelliJ IDEA, Matt needed a framework to manage tabs and docking. As he didn’t find the perfect solution, he created the library BentoFX. Another nice visualization library he created for Recaf, is TreeMapFX, a flexible tree map chart control for JavaFX. Next to these libraries, Matt also created GLCanvas-FX, a small project showing a single basic JavaFX control used to display OpenGL content from an JOGL GLAutoDrawable. They are demonstrated in the interview, and available on GitHub.

More info in this blog post.

Craig Raw: Sparrow Bitcoin Wallet

Craig Raw is the creator of the Sparrow Bitcoin Wallet. He lives in South Africa. Funny fact: in the video, you can hear that he is surrounded by birds who wanted to join the conversation. Craig loves Java and JavaFX because of how easy it is to create user-friendly interfaces. He also values the security built into Java. Another important aspect for him is the ability to create reproducible builds, a key factor in the security of the Bitcoin ecosystem.

Sparrow is a Bitcoin wallet for those who value financial self sovereignty. Sparrow’s emphasis is on security, privacy and usability. Sparrow does not hide information from you - on the contrary it attempts to provide as much detail as possible about your transactions and UTXOs, but in a way that is manageable and usable.

Sparrow supports all the features you would expect from a modern Bitcoin wallet, however, it is also unique in that it contains a fully featured transaction editor that also functions as a blockchain explorer. This feature not only allows editing of all transaction’s fields, but also allows you to easily inspect the transaction bytes before broadcasting.

More info in this blog post.

Florian Enner: Robot 3D Visualizations and Charts

Florian Enner works on software libraries and applications that are aimed at simplifying development of robotic systems. For example, he has worked on an API for MATLAB that is capable of low-latency real-time control of high degree of freedom systems. It allows engineers without a strong background in computer science to develop sophisticated control algorithms without requiring knowledge of C/C++ or code generation.

In the video, Florian shows some of the JavaFX applications he has created to visualize the movements of robots in a 3D environment and the measurements of sensors in charts capable of rendering millions of data points. Based on the same code, he has created desktop and mobile applications that can receive the UDP messages directly from the devices and render the same charts and 3D.

He also demonstrates styling with AtlantaFX, the use of SceneBuilder, and how he compiles JavaFX views to native libraries so they can be integrated in C/C++ projects to visualize big amounts of data.

More info in this blog post.

The post Video series “JavaFX In Action”, Part 6 with Vlad Protsenko (Clojure), Matt Coley (Recaf), Craig Raw (Sparrow), and Florian Enner (3D Robot Visualization) appeared first on foojay.

This is the next part in the series of "JavaFX in Action" interviews. Are you working on a fantastic JavaFX application? Let me know, and let's discuss it in the new year!

• July '24: Pedro Duque Vieira, Daniel Zimmermann, Christopher Schnick, and Robert Ladstätter
• November '24: Maciej Gorywoda, Ramiro Domínguez Ayub, Christoph Schwentker, Ulas Ergin
• December '24: Özkan Pakdil, Clément de Tastes, Almas Baim, Steve Hannah, Jago de Vreede
• March '25: Mike Hearn, Sven Reimers, Chris Newland

Cormac Redmond: KafkIO, the Kafka UI for Engineers and Admins

Cormac Redmond is an “All-things Java / Spring / MicroServices” expert who has been computing and programming from a young age. He has 20 years of professional experience spanning several industries, building everything from complex distributed systems to bespoke intranets and mobile apps. He enjoys fully and deeply understanding any domain or technology and is happiest when working within cultures that value the importance of building clean, elegant, testable, self-documenting systems while adopting forward-thinking practices and techniques.

KafkIO is designed for easy, fast, and enjoyable use. It only takes a few clicks before you’re exploring your Kafka clusters. No web servers, configuration files, clunky installation, Docker, or funky licensing! You can seamlessly create/edit/delete/dump/clear topics, produce messages, advanced search and streaming with text, offset, and date range criteria, tweak offsets, delete consumers, and browse/create/update schemas. Easily manage access control lists (ACLs). View your data in a variety of ways. Manage Kafka Connect connectors and ksqlDB (with a flexible KSQL editor). Troubleshoot issues with a clear view of the broker, topic, ksqlDB, connector, and consumer configuration, with live statistics such as partition skew, out-of-sync replicas, consumer lag, etc.

The UI is created with JavaFX and uses different libraries, which are all styled in a very consistent and easy-to-understand way. The application is beautifully designed and an excellent showcase of what can be achieved if a Java backend and JavaFX user interface are combined in one single powerful application!

More info in this blog post.

Brian Schlining: Annotating the Deep-Sea Wildlife

Brian Schlining is a Software Engineer at the Monterey Bay Aquarium Research Institute (MBARI), specializing in designing software systems to support scientific research. This includes data systems design, database development, user interface development (desktop and web applications), GIS, image and video analysis, micro-services, and analysis of large data sets.

Within MBARI, a full system of micro-services has been developed to store a large number of deep-sea videos and images, a knowledge base about the animals living in the sea, machine learning tools, etc.

VARS Annotation is a JavaFX user interface for creating and editing video annotations. It targets modern video workflows and is part of the MBARI Media Management software stack. It’s not a standalone application but depends on several external services that need to be deployed.

More info in this blog post.

Gerrit Grunwald: Creator of Many Amazing JavaFX Libraries

Gerrit Grunwald loves coding for around 40 years already. He is interested in desktop, mobile and IoT projects based on all possible technologies. But above all, he loves all-things-Java. He is the founder and leader of the Java User Group Münster (Germany), JavaOne rockstar and Java Champion. As Developer Advocate at Azul, he speaks a lot at conferences and user groups all around the world.

In the video, we discuss some of the libraries Gerrit has created, but there are a lot more! Check his GitHub repositories and blog…

• GitHub repositories
  • TilesFX: A JavaFX library containing tiles for Dashboards.
  • Medusa: A JavaFX library for Gauges.
  • Charts: A library for scientific charts in JavaFX.
  • and much more…
• Personal blog Harmonic Code
• Blog posts on Foojay.io

More info in this blog post.

Dirk Lemmermann: Creator of JavaFX Libraries and Applications

Dirk Lemmermann has over 40 years of programming and 30 years of professional experience. He is a seasoned and passionate software engineer and leader with a master’s degree in computer science and multiple honors and awards for his work in UI development and design, tool development, and scheduling applications.

As the CEO of Senapt and DLSC, he oversees the development of CRM systems for energy suppliers in England and Java and JavaFX consulting and software development for various domains and applications. His mission is to deliver high-quality, innovative, and user-friendly solutions that meet the needs and expectations of his clients and partners.

JavaFX Libraries

Dirk has created, or contributed to, a lot of libraries, and most of them are available as open source libraries!

• FlexGanttFX
• ControlsFX
• GemsFX
• WorkbenchFX
• CalendarFX
• GitHub repositories with more work by Dirk

JFX Central

JFX Central, the home to anything JavaFX related, is a website, desktop application, and mobile app, all based on the same code base. Both the tool itself, as the data it uses, are open source projects.

• JFX Central, website
• JFX Central, sources
• JFX Central, data sources

Senapt Applications

Senapt provides “Energy-as-a-Service Platform”, by providing an energy transactions platform for energy sellers and energy buyers in the UK. As the energy landscape has continued to change, retail electricity providers have been looking for strategies to meet the ever-growing, ever-changing demands for their customers. Senapt’s products have been designed to help energy suppliers to facilitate this changing relationship and allow them to seize the opportunities of the smart grid.

More info in this blog post.

The post Video series “JavaFX In Action”, Part 5 with Cormac Redmond (KafkIO), Brian Schlining (Annotating the Deep-Sea Wildlife), Gerrit Grunwald (JavaFX Libraries), Dirk Lemmermann (JavaFX Libraries and Applications, JFX Central) appeared first on foojay.

Please follow us on LinkedIn and/or YouTube for the live interviews.

Just like last year, these interviews will be grouped into podcast episodes, so stay tuned for more Java knowledge sharing!

The post Foojay Live @ JCON Köln appeared first on foojay.

We are celebrating Java's 30th anniversary this May!

This is a very special anniversary episode of the Foojay Podcast! As we approach May 23rd, marking exactly 30 years since Java's first beta release in 1995, we're honored to present our first-ever single-guest podcast. But we have a very special guest for you: James Gosling, the creator of Java!

Join us for this exclusive conversation as we explore Java's beginnings, its revolutionary impact on the programming world, its continuous evolution over three decades, and James's insights on where the language is heading. From that groundbreaking beta release over "Write Once, Run Anywhere" to powering billions of devices worldwide, this is the story of Java, told by the man who started it all, the father of Java.

Video

Podcast Apps

You can listen and subscribe to the Foojay Podcast on:

• Spotify
• Apple Podcasts
• And most others...

Content

00:00 Introduction
01:06 How did it start 35 years ago?
06:21 Java evolved from device controllers to server applications
10:30 How does it feel that so many people use Java?
12:12 Looking back at the Y2K problem and how it triggered more Java adoption
14:58 Does James regret any decisions in Java?
18:44 Comparing early-day Java development versus now
20:55 About the stability of Java
24:14 JavaFX is one of James' favorites of all time
25:20 Frustrations about Android and iOS versus Java Phones
28:16 How "Write Once, Run Anywhere" was needed for Sun
29:23 Windows versus macOS versus Linux for laptops
31:32 The very first Java web service in 1994 turned into a dark story
33:17 Java in Docker and startup challenges
36:59 Garbage Collectors are amazing in many ways
39:18 Java-haters didn't use recent versions of Java ...
41:51 How Java became much more performant but lost embedded
43:08 Developers must be aware of which and how many libraries they use
47:40 James loves Kotlin, Scala, and Closure
49:42 Ethical responsibility for developers in a challenging job market
54:16 AI influence on jobs
01:00:20 Advice for junior developers
01:02:27 A few of the most remarkable moments in Java history
01:07:52 Why James is not a benevolent dictator for life
01:09:17 How Java will keep evolving
01:12:55 How much is James still involved in Java?
01:13:54 Conclusion

The post Foojay Podcast #71: Celebrating 30 Years of Java with James Gosling appeared first on foojay.

This is the next part in the series of "JavaFX in Action" interviews. Are you working on a fantastic JavaFX application? Let me know, and let's talk!

• July '24: Pedro Duque Vieira, Daniel Zimmermann, Christopher Schnick, and Robert Ladstätter
• November '24: Maciej Gorywoda, Ramiro Domínguez Ayub, Christoph Schwentker, Ulas Ergin
• December '24: Özkan Pakdil, Clément de Tastes, Almas Baim, Steve Hannah, Jago de Vreede

Mike Hearn: Conveyor, build self-updating desktop app packages

Mike Hearn solves a problem many developers are struggling with: efficiently distributing your application and ensuring the users get the latest version. With Conveyor, he created a tool that can do that easily with JavaFX, Electron, and Flutter apps!

Conveyor makes distributing desktop apps as easy as shipping a web app. It’s a tool, not a service, that generates and signs self-upgrading packages for Windows, macOS, and Linux using each platform’s native package formats without requiring you to have those operating systems.

It’s free for open-source apps and has simple per-project pricing for commercial apps.

More info in this blog post.

Sven Reimers: JTaccuino, notebook application for Java developers

Sven Reimers created a JavaFX-based notebook application to make it easier to learn Java and experiment with notebooks that can visualize the variables differently, such as tables and graphs.

JTaccuino is a JavaFX-based notebook application for Java developers. It is built for usages in education, interactive experimentation with algorithms, and more advanced use cases. JShell, the awesome Java REPL, provides Java code execution.

More info in this blog post.

Chris Newland: DemoFX and JitWatch

Chris Newland has a long history of Java and JavaFX development. I invited him to talk about two of his JavaFX projects: DemoFX and JITWatch. While the demos are impressive already, Chris also gives a “crash course” in this video about Java and Byte code and how the Just-In-Time compiler converts these to native code in the Java Virtual Machine.

DemoFX is a performance test platform for JavaFX. It can layer and schedule effects on a timeline. It is used to discover the best techniques to optimize JavaFX performance on the Raspberry Pi and Desktop.

JITWatch is a log analyser and visualiser for the HotSpot JIT compiler. It helps you to inspect inlining decisions, hot methods, bytecode, and assembly. You can view the results in a JavaFX user interface.

More info in this blog post.

The post Video series “JavaFX In Action”, Part 4 with Mike Hearn (Conveyor), Sven Reimers (JTaccuino), and Chris Newland (DemoFX, JitWatch) appeared first on foojay.