GenAI on foojay.io - Friends of OpenJDK

Why Spring Teams Don't Need a Second Runtime for AI Agents

Wed, 10 Jun 2026 19:02:58 +0000

A JVM-native runtime for building, governing and operating AI agents on existing Spring infrastructure.

Every time a Spring team decides to add AI agents to a production system, the story tends to follow the same arc. A few prototypes are built, several frameworks are evaluated, and then a new reality emerges: the project is no longer just about adding agents. It is about operating a new platform.

With that new runtime come new deployment pipelines, new monitoring mechanisms, additional security reviews, and new operational responsibilities.

Context Is Code: A Tour of APM and AgentRC

Fri, 05 Jun 2026 08:35:05 +0000

If you’ve shipped an AI agent into a real codebase in the last twelve months, you’ve felt this: every agent, every developer, every machine — different setup. A README that says “install these extensions.” A copilot-instructions.md somebody copy-pasted from another repo. MCP server configs in three different files. The same skills duplicated for Copilot, Claude, Cursor, and Codex.

No version pinning.

No integrity.

No reproducibility.

That’s the problem APM , the Agent Package Manager fixes. And it pairs with AgentRC to close the loop on generating and evaluating that context in the first place.

Tiberius: A Security Testing Framework for LLM Applications in Java

Thu, 04 Jun 2026 20:09:09 +0000

How do you write a regression test for a system that is non-deterministic by design?

The Problem {#h2-0-1-the-problem}

Large Language Models have moved from research artifacts to production infrastructure. Java applications are embedding them into customer-facing services via Spring Boot, and e.g. LangChain4J — for document summarization, customer support, healthcare assistance, and financial guidance, to name just a few. The deployment surface is growing faster than the security tooling.

The vulnerability landscape is empirically well-established. Horlacher, Vifian, and Zagidullina (2026) [4] red-teamed gpt-oss-20b and found that adversarial techniques achieved alarmingly high Attack Success Rates, while non-adversarial probing exposed pervasive stereotypical defaults — both consistent across English and Swiss German. Their conclusion: “current alignment mechanisms have not fully resolved jailbreaks and inherent bias, posing critical challenges for automated decision-making.”

BoxLang AI 3.2.0 — Image Generation, Web Search, Fluent Audio, Agent Registry & MCP Observability

Tue, 02 Jun 2026 12:27:07 +0000

BoxLang AI 3.2.0 is here, and it’s a landmark release. We’re shipping five major features: image generation, web search, a fluent audio builder API, a centralized agent registry, and deep MCP observability along with a suite of analytics improvements and a critical bug fix. Let’s dig in. 🎉

🖼️ Image Generation — aiImage()

You can now generate images directly from BoxLang using any provider that supports text-to-image generation. The aiImage() BIF follows the same fluent, chainable philosophy as the rest of bx-ai then act on the result with expressive method calls.

Free Webinar: Making AI useful for Java developers in Real Applications with BoxLang!

Fri, 29 May 2026 15:43:47 +0000

AI is everywhere right now, but for many development teams, the biggest question is no longer “What is AI?” it’s “How do we actually use it in real applications in a secure, practical, and maintainable way?”

That’s exactly what we’ll explore in our upcoming free June webinar:

Making AI Useful in Real Applications

A Practical Guide to Secure and Effective AI Development

Join Bill Reese, Senior Developer at Ortus Solutions , for a practical session focused on bringing AI into real-world applications using BoxLang and modern JVM development patterns.

Introducing skills.boxlang.io — The Open Agent Skills Ecosystem for BoxLang & the Ortus World

Thu, 21 May 2026 11:42:26 +0000

Today we’re launching something we’ve been quietly building for months: skills.boxlang.io — a public, agent-agnostic directory for AI skills covering BoxLang, ColdBox, TestBox, CommandBox, and the entire Ortus ecosystem.

If you’ve ever pasted a 400-line system prompt into yet another AI agent, watched two of your bots drift onto subtly different versions of the same coding standard, or spent half a Friday afternoon trying to convince an LLM that BoxLang is not Java and is not CFML, or how to code for Modern CFML; this launch is for you. 🎯

BoxLang AI Series: Complete Guide to Building AI Agents

Thu, 14 May 2026 09:26:48 +0000

The world of AI development is moving fast, but building real, production-ready AI agents doesn’t have to be complex.

This series walks you step by step through how to design, build, and deploy AI agents using BoxLang AI. Whether you’re exploring AI for the first time or looking to modernize your current applications, these guides will help you move from concept to implementation with clarity.

Start Here: A Practical Overview

If you’re new to BoxLang AI or want to understand what’s possible before diving into the technical details, start here:

How to Develop AI Agents Using BoxLang AI: A Practical Guide

Tue, 12 May 2026 12:52:39 +0000

AI agents are transforming how we build software. Unlike traditional chatbots that just answer questions, agents can reason about what tools they need, decide when to use them, chain multiple actions together, and remember what happened earlier in a conversation.

In this tutorial, I’ll show you how to build a real-world AI agent using BoxLang AI — the official AI framework for the BoxLang JVM language. We’ll build SupportBot, an e-commerce customer support agent that can look up orders, check inventory, issue refunds, and answer questions grounded in your knowledge base.

BoxLang AI Deep Dive — Part 7 of 7: MCP — The Protocol That Connects Everything

Thu, 07 May 2026 21:51:08 +0000

BoxLang AI 3.0 Series · Part 7 of 7

The AI ecosystem has a tool problem. Every framework has its own way of defining tools, every agent has its own way of calling them, and every integration requires custom code on both sides. An agent built in Python can’t easily use tools built in Java. An MCP server written for Claude Desktop can’t easily be consumed by a BoxLang agent without a custom adapter.

BoxLang AI Deep Dive — Part 6 of 7: Memory Systems & RAG — Building AI That Remembers

Tue, 05 May 2026 15:10:15 +0000

BoxLang AI 3.0 Series · Part 6 of 7

A chatbot with no memory isn’t a conversation — it’s a series of isolated queries. Every message starts from scratch. The user has to re-explain who they are, what they’re working on, and what was just said. It’s exhausting, and it signals that the AI isn’t really listening.

Memory is what separates a useful AI application from a toy. BoxLang AI ships with one of the most comprehensive memory systems in any AI framework — 20+ memory types across two major categories, vector embedding support for semantic retrieval, 30+ document loaders for RAG pipelines, and a per-call identity routing system that makes multi-tenant applications safe by default.

BoxLang AI Deep Dive — Part 5 of 7: One API, 17 Providers — The Provider Architecture Deep Dive

Wed, 29 Apr 2026 16:38:08 +0000

BoxLang AI 3.0 Series · Part 5 of 7

Vendor lock-in is the silent killer of AI projects. You pick OpenAI, build everything against the OpenAI API, and then GPT-5 launches at three times the price. Or a competitor launches a model that’s faster for your use case. Or you need to self-host for compliance. Or your client is on AWS and wants Bedrock.

Every time the answer to “can we switch providers?” is “it would take months,” something went wrong architecturally.

Explore Spring AI SDK – Amazon Bedrock AgentCore – Part 2

Mon, 27 Apr 2026 09:09:00 +0000

If you’re joining us from Part 1 or need a quick refresher on the architecture, listen to this brief overview of how Spring AI and Amazon Bedrock work together. Generated using Notebook LLM for my previous article {#https://foojay.io/today/spring-ai-amazon-bedrock-sdk-guide/}

In this article, we explore one of the AgentCore capabilities i.e., memory Source: Amazon

To begin, enable AgentCore memory for the agent you built earlier.

Step 1: Add the Ai model and AgentCore memory dependencies

<dependency>
 <groupId>org.springframework.ai</groupId>
 <artifactId>spring-ai-model</artifactId>
</dependency>
<dependency>
 <groupId>org.springaicommunity</groupId>
 <artifactId>spring-ai-agentcore-memory</artifactId>
</dependency>

Step 2: Create Short/Long Term in AWS Management Console

Navigate to Amazon Bedrock AgentCore > Memory to create short/long-term memories. AgentCore Memory

BoxLang AI Deep Dive — Part 4 of 7: Middleware — The Missing Layer in Every AI Framework 🧵

Thu, 23 Apr 2026 14:25:53 +0000

BoxLang AI 3.0 Series · Part 4 of 7

Here’s the question every team eventually asks about their AI agents: how do we test these things?

Agents make live LLM calls. They invoke real tools. They have non-deterministic outputs. Standard unit testing approaches fall apart. You can’t mock every provider. You can’t replay a conversation from three weeks ago. You can’t confidently tell stakeholders that the agent you deployed today behaves the same way it did when you signed off on it.

BoxLang AI Deep Dive — Part 3 of 7: Multi-Agent Orchestration — Building AI Teams That Work 🌲

Tue, 21 Apr 2026 08:32:06 +0000

BoxLang AI 3.0 Series · Part 3 of 7

A single agent is useful. An orchestra of agents is powerful.

The problem with most multi-agent frameworks is that the orchestration layer is bolted on — you’re managing agent references manually, passing outputs between them by hand, and hoping you haven’t introduced a cycle. There’s no concept of hierarchy. No cycle detection. No way to ask “who’s in charge here?” or “how deep in the tree am I?”

Explore Spring AI SDK - Amazon Bedrock AgentCore - Part 1

Mon, 20 Apr 2026 13:44:54 +0000

Introduction

Artificial intelligence has rapidly expanded across every industry since the inception of ChatGPT. It represents a breakthrough in how we build and use software. Moreover, this breakthrough technology has driven major transformation. At the same time, it has created significant noise and hype.

Today, AI is no longer experimental. Instead, it has become essential, much like electricity and the internet. As a result, it now plays a key role in our daily lives. Overall, this shift reflects strong technological acceleration across industries.

BoxLang AI Deep Dive — Part 2 of 7: Building a Production-Grade AI Tool Ecosystem

Thu, 16 Apr 2026 09:27:15 +0000

BoxLang AI 3.0 Series · Part 2 of 7

Function calling is where most AI frameworks look deceptively simple on the surface and turn into a mess underneath. You define a tool, pass it to the LLM, and when the LLM calls it — who handles the lifecycle? Who fires observability events? Who serializes the result? Who resolves the tool by name when the only thing you have is a string?

BoxLang AI Deep Dive — Part 1 of 7: The Skills Revolution 🎓

Tue, 14 Apr 2026 11:50:53 +0000

This article is part of our 7-part deep dive on building production-ready AI systems with BoxLang.

BoxLang AI 3.0 Series · Part 1 of 7

Every AI framework eventually hits the same wall: your system prompts start drifting. Agent A has a slightly different version of the SQL rules than Agent B. The tone policy on your support bot is three weeks behind the tone policy on your documentation bot. Someone copy-pasted the wrong version. Nobody noticed.

BoxLang AI v3 Has Landed - Multi-Agent Orchestration, Tooling, Skills and so much more

Mon, 06 Apr 2026 12:03:58 +0000

It’s been a while since we’ve shipped something this big. BoxLang AI 3.0 is a ground-up rethink of how AI agents, models, and tools work in the BoxLang ecosystem — and it lands with ten major features at once.

The headline is the AI Skills system : a first-class implementation of Anthropic’s Agent Skills open standard that lets you define reusable knowledge blocks: coding styles, domain rules, tone policies, API guidelines once in a SKILL.md file and inject them into any number of agents and models at runtime. No more copy-pasting the same system-prompt boilerplate everywhere. Skills are versioned, composable, and come in two modes: always-on (full content in every call) and lazy (only a name + description until the LLM asks for more).

From “Crypto AI” to general AI: Do AI agents dream of electric langoustines?

Mon, 23 Feb 2026 18:11:54 +0000

A Blade Runner riff for a world where the lobster ships paid endpoints while humans still argue about the roadmap.

The shift that matters for agent commerce - From “Crypto AI” to general AI

Today, you can search the web all day and never see an invoice.

That happens because you are not the paying client.

The commerce runs through ads, affiliate deals, and platform incentives, so results often optimize for who pays, not for what you asked for.

DevBcn, the developer's conference in Barcelona

Tue, 17 Feb 2026 09:56:33 +0000

Hola developers !!!!!

The 11th edition of DevBcn , the developer’s conference in Barcelona is coming next June. The perfect place to have great technology talks 🤖, perfect weather 🏖️, amazing food 🥘, and an unforgettable experience 💖.

It will be hosted on the 16th and 17th of June 2026, in the World Trade Center Conference Center , having 4 rooms with talks in parallel during the 2 days of the conference : Java/JVM, AI, Cloud, Frontend, Managing and Soft skills.

Windsurf AI and SonarQube The Dream Team for AI Code Quality

Mon, 16 Feb 2026 09:34:00 +0000

Hola! 👋 As a Java developer, you probably spend a good chunk of your day making sure your code doesn’t just “work,” but is also maintainable, secure, and reliable. I’ve been using a tool that is changing how I handle large projects: Windsurf.

It is an agentic IDE that understands what you are trying to do across your whole project. Let’s see why this is a game-changer for our Java workflows. 🚀

Join Our Webinar: Build Agents, RAG Pipelines and More

Tue, 10 Feb 2026 12:18:17 +0000

Build Agents, RAG Pipelines & Multi-Model Workflows — One API, Zero Lock-In

Modern enterprises want to move fast with AI—but juggling different providers, SDKs, formats, and deployment models quickly becomes complex and brittle.

That’s why we’re excited to announce our upcoming webinar:

Unlock Enterprise AI on the JVM: Build Agents, RAG Pipelines & Multi-Model Workflows with BoxLang AI One API, Zero Lock-In Led by Luis Majano

In this session, you’ll discover BoxLang AI , an open-source library that brings unified, fluent AI orchestration to the JVM ecosystem. With a single, intuitive API, BoxLang AI lets you integrate 12+ leading AI providers (including OpenAI, Claude, Gemini, Grok, Ollama, Groq, and more), switch models, or combine them into advanced workflows—without rewriting your code.

JC-AI Newsletter #13

Thu, 05 Feb 2026 21:12:12 +0000

Two weeks have passed, and it is time to present a new collection of readings that may shape developments, utilization or ideas in the field of artificial intelligence in 2026.

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.

Claude Code SonarQube MCP: A Java Developer’s Workflow

Mon, 02 Feb 2026 15:15:17 +0000

Hola Java developers! 👋

We all know the feeling. You are “in the zone,” coding away in your terminal, feeling like a hacker from a 90s movie. But then, reality hits. You need to check a rule, review a vulnerability, or verify if your project passes the quality gate.

What do you do? You Alt+Tab. You open the browser. You log in. You search. And just like that… the flow is gone. 📉

DocBox v5 - Reborn: Modern API Docs for BoxLang & CFML

Tue, 27 Jan 2026 12:15:45 +0000

Welcome to DocBox v5! We didn’t just update DocBox. We rebuilt it from the ground up.

DocBox v5.0.0 represents a complete architectural rewrite—modern syntax, blazing performance, and a stunning new look that finally brings API documentation into 2025. Gone are the clunky HTML pages of yesteryear. Say hello to a gorgeous, theme-driven single-page application that makes browsing your API docs feel like using a premium developer tool. We have also released a dedicated module for BoxLang: BX-DOCBOX. A fully interactive CLI tool for generating your docs from the command line using pure BoxLang.

BoxLang AI v2: Enterprise AI Development Without the Complexity

Thu, 22 Jan 2026 15:09:25 +0000

One Year. 100+ Features. Unlimited Possibilities.

Just one year ago, in March 2024, we launched BoxLang AI 1.0. Today, we’re thrilled to announce BoxLang AI v2—a massive leap forward that positions BoxLang as one of the most powerful and versatile AI framework on the JVM. This release is 9-months in the making, with over 100 new features! This would have not been possible without all the new features that the BoxLang JVM language exposes to developers like: Server Side Events, HTTP Streaming, HTTP pooling, Caching, and so much more.

JC-AI Newsletter #12

Wed, 14 Jan 2026 07:15:44 +0000

F irst of all, Happy New Year 2026! This year is designated in the Chinese Calendar as the Year of the Fire Horse (starting on February 17.). The year 2026 brings not only tremendous energy to AI development but also, in my humble opinion, many breakthroughs in the field.

Although there have been many small steps toward the field’s evolution, it often feels that development is stagnating, applying known or slightly tweaked strategies to non-deterministic problems while expecting deterministic results. This includes the often misleading benchmarking strategies (deterministic) performed on synthetic datasets.

Not a Lucid Web3 Dream Anymore: x402, ERC-8004, A2A, and The Next Wave of AI Commerce

Fri, 09 Jan 2026 16:05:58 +0000

This article is for technically savvy readers, especially developers, protocol designers, and product teams working with AI agents, APIs, or crypto rails, who want a clear view of how these areas connect.
It explains how x402, ERC-8004, and agent discovery layers turn APIs and agents into small usage-based businesses, and what that means for real systems over the next 1–3 years.

Vocabulary for this article

In this article, I use the term micro business for a very small overall business, and nano business for a single x402-priced endpoint or agent that earns on its own from per-call payments in stablecoins.

AP2 (Agent Payment Protocol): AP2 defines how agents pay each other. It standardizes how a service quotes a price, how payment is confirmed, and how both sides record what was bought, so payments fit directly into automated agent workflows. In practice, it is a protocol that lets one machine pay another machine for work, without a human in the loop.

A2A (Agent-to-Agent communication): A2A covers how agents talk, pass context, and coordinate work. It lets agents call each other, exchange structured messages, and chain tasks instead of acting as isolated scripts.

x402: x402 is an HTTP-based payment protocol for APIs. A server responds with status 402 Payment Required, the price, and a payment route, and the client pays by using stablecoins on-chain and then retries the request to get the result.

ERC-8004 (8004): ERC-8004 standard is an on-chain registry for agents. It gives each agent an identity and a place to store reputation data, so other agents and tools can decide whom to trust and which services to call.

Foreword

x402 and ERC-8004 .

The End of One-Sized-Fits-All Prompts: Why LLM Models Are No Longer Interchangeable

Sun, 14 Dec 2025 18:48:31 +0000

For developers and product builders, one assumption has guided the last few years of LLM application development. To improve your product, just swap in the latest frontier large language model. Flip a single switch and your tool’s capabilities level up.

But that era is over. We’re now seeing that new models like Anthropic’s Claude Sonnet 4.5 and OpenAI’s GPT-5-Codex have diverged in fundamental ways. The choice of which model to use is no longer a simple engineering decision but a critical product decision. Flip that switch today… and the very texture of your product changes.

JC-AI Newsletter #11

Tue, 09 Dec 2025 16:12:01 +0000

Fourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of artificial intelligence.

This newsletter explores the evolution of agentic AI systems, provides valuable insights into the Chain-of-Thought (CoT) approach, Vibe coding, and discusses the pattern-matching capabilities of LLMs. The newsletter features an insightful interview with Stuart J. Russell, known for his significant contributions to the AI field. Even more exciting is the published paper by Apple researchers titled ‘The Illusion of Thinking…’ and several immediate reactions to the authors’ conclusions, which allow newsletter readers to observe current research challenges and scientific community responses. This provides readers with a vital picture of the state-of-the-art in AI research.

JC-AI Newsletter #10

Wed, 26 Nov 2025 18:39:40 +0000

Fourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of artificial intelligence.

This newsletter focuses on examining how agentic AI systems improve accuracy, tutorials on agentic system architecture, and importnat security challenges arising from increased not only from agentic AI systems adoption. This edition of the AI newsletter includes compelling discussions and interviews about the future of AI and approaches.

JC-AI Newsletter #9

Wed, 12 Nov 2025 15:21:12 +0000

Fourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of artificial intelligence.

This newsletter focuses on examining how AI enhances productivity through enterprise studies, tutorial, agentic system architecture, GraphRAG, evaluating risk methodologies in agentic systems, and the security challenges arising from increased AI-LLM adoption. This edition of the AI newsletter includes a compelling discussion between six of the most influential leaders in artificial intelligence, along with additional content.

A Guide to SonarQube MCP Server on IntelliJ

Fri, 07 Nov 2025 17:00:24 +0000

Hey Java devs! 👋 Ever feel like you’re drowning in a sea of code, trying to keep it reliable,, efficient, and secure? We’ve all been there. Juggling new features, bug fixes, and pull requests is a daily grind. But what if you had an AI-powered assistant to help you out? That’s where the SonarQube MCP Server comes in. Let’s dive into how this cool new MCP can supercharge your daily coding routine. 🚀

JC-AI Newsletter: Easy Access to Expanding Challenges

Tue, 04 Nov 2025 18:13:33 +0000

A few months ago, I launched the AI Newsletter to provide a minimally biased perspective on the growing challenges surrounding artificial intelligence.

My primary motivation was and remains to be serving the community not only by showing how to use and access specific services for utilizing Large Language Models, but also by support a deeper understanding of the broader artificial intelligence landscape.

Many of the core challenges that have emerged around LLMs have not been and still not properly addressed, often omitted due to their uncomfortable implications.

JC-AI Newsletter #8

Thu, 30 Oct 2025 06:36:12 +0000

Fourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of artificial intelligence.

This newsletter focuses on examining how AI enhances productivity through enterprise studies, agentic system architecture, attack vectors, Model Context Protocol (MCP) implementation, Agent-to-Agent (A2A) protocol, Java code generation within IDEs, LLM benchmarking methodologies, and the security challenges arising from increased AI-LLM adoption.

The world influenced by LLM is changing very quickly, let’s start…

7 habits of Highly Effective Java Coding

Wed, 15 Oct 2025 11:25:03 +0000

From AI User to AI Pro

Let’s be real, AI coding tools are everywhere now. 🤖 They’re no longer some shiny new toy—they’re a part of our daily grind as developers, just like our morning coffee. ☕

For us Java devs, whether we’re wrestling with a giant legacy app or juggling a bunch of microservices, these tools look like a huge win for getting stuff done faster. 🚀

But here’s the catch: just coding faster isn’t the whole story. If you’re not careful, it can actually lead to bigger problems down the road. 🤔

JC-AI Newsletter #5

Thu, 18 Sep 2025 07:19:33 +0000

Fourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of artificial intelligence.

Beyond opinion pieces and Java focused tutorials that can enhance your understanding of AI applications, this newsletter concentrates on LLM benchmarking methodologies designed to ensure models accuracy and competency in handling complex contextual information.

The world influenced by LLM is changing very quickly, let’s start…

JC-AI Newsletter #4

Tue, 02 Sep 2025 20:27:52 +0000

14 days have passed and it’s time for a new batch of readings that could shape developments in the field of artificial intelligence.

The current newsletter vol. 4 offers us a closer look at several different areas of artificial intelligence. We start with the topic of energy consumption and the environmental impact of systems serving artificial intelligence, and continue with automation, how we obtain data for RAG, robustness of GenAI systems, vibe-coding and more.

JC-AI Newsletter #3

Tue, 19 Aug 2025 08:06:34 +0000

The first and second newsletters introduced a 14-day cadence, and even though it is the holiday season for many of us, we are sticking to the promised period.

The current newsletter vol.3, brings a collection of valuable articles focusing on challenges that are commonly reported through reported breakthroughs in the field of artificial intelligence. Although some articles may remain open or contain suggestions for future research due to the intensive development and utilization efforts of agentic AI systems, these articles can be considered valuable to the community, increasing awareness and understanding of ongoing challenges.

New Java Benchmark for Coding LLMs puts GPT-5 at the top

Mon, 18 Aug 2025 08:06:40 +0000

The Brokk Power Ranking is a new open-source coding benchmark , featuring 93 tasks from large, real-world codebases. You can check out the current Power Ranking here .

SWE-bench is the closest thing we have to a standard, objective benchmark for LLM coding performance, but it has a bunch of issues, the largest of which are that it’s Python-only, and it’s old enough that almost certainly some labs are now training to the test. (Epoch AI has a great writeup on the more subtle problems with SWE-bench if you want to go deeper.)

JC-AI Newsletter #2

Tue, 05 Aug 2025 06:30:03 +0000

The JC-AI Newsletter Vol.2 brings again a very interesting collection of articles worth considering.

The world influenced by LLM is changing very quickly, let’s start…

article: OpenAI CEO Sam Altman warns of an AI ‘fraud crisis’

author : Clare Duffy, CNN
date : 2025-07-22
desc.: Sam Altman discusses the serious potential for current AI abuse. Although the example of attacks on financial institutions is mentioned, Sam Altman warns of the broader impact before one even takes advantage of LLM agent systems.

AI Newsletter #1

Tue, 22 Jul 2025 05:39:26 +0000

There is a lot going on in today’s technological world, but the most intense and vibrant area is undoubtedly the field of artificial intelligence. After brainstorming, our Java Champion Education group agreed to create a newsletter with a 14 days cadence. In our newsletters, we will include a collection of recently read interesting resources in the field of artificial intelligence with a short description.

Although the stream of published articles is very large and the ability to read them all is an illusion, the published selection, such as the below is implicitly narrowed. The purpose of the AI Newsletter is to help everyone stay informed and expand their knowledge in areas related to artificial intelligence.

GenAI on foojay.io - Friends of OpenJDK

Why Spring Teams Don't Need a Second Runtime for AI Agents

Context Is Code: A Tour of APM and AgentRC

Tiberius: A Security Testing Framework for LLM Applications in Java

BoxLang AI 3.2.0 — Image Generation, Web Search, Fluent Audio, Agent Registry & MCP Observability

Free Webinar: Making AI useful for Java developers in Real Applications with BoxLang!

Making AI Useful in Real Applications

A Practical Guide to Secure and Effective AI Development

Introducing skills.boxlang.io — The Open Agent Skills Ecosystem for BoxLang & the Ortus World

BoxLang AI Series: Complete Guide to Building AI Agents

Start Here: A Practical Overview

How to Develop AI Agents Using BoxLang AI: A Practical Guide

BoxLang AI Deep Dive — Part 7 of 7: MCP — The Protocol That Connects Everything

BoxLang AI Deep Dive — Part 6 of 7: Memory Systems & RAG — Building AI That Remembers

BoxLang AI Deep Dive — Part 5 of 7: One API, 17 Providers — The Provider Architecture Deep Dive

Explore Spring AI SDK – Amazon Bedrock AgentCore – Part 2

Step 1: Add the Ai model and AgentCore memory dependencies

Step 2: Create Short/Long Term in AWS Management Console

BoxLang AI Deep Dive — Part 4 of 7: Middleware — The Missing Layer in Every AI Framework 🧵

BoxLang AI Deep Dive — Part 3 of 7: Multi-Agent Orchestration — Building AI Teams That Work 🌲

Explore Spring AI SDK - Amazon Bedrock AgentCore - Part 1

Introduction

BoxLang AI Deep Dive — Part 2 of 7: Building a Production-Grade AI Tool Ecosystem

BoxLang AI Deep Dive — Part 1 of 7: The Skills Revolution 🎓

BoxLang AI v3 Has Landed - Multi-Agent Orchestration, Tooling, Skills and so much more

From “Crypto AI” to general AI: Do AI agents dream of electric langoustines?

The shift that matters for agent commerce - From “Crypto AI” to general AI

DevBcn, the developer's conference in Barcelona

Windsurf AI and SonarQube The Dream Team for AI Code Quality

Join Our Webinar: Build Agents, RAG Pipelines and More

JC-AI Newsletter #13

Claude Code SonarQube MCP: A Java Developer’s Workflow

DocBox v5 - Reborn: Modern API Docs for BoxLang & CFML

BoxLang AI v2: Enterprise AI Development Without the Complexity

JC-AI Newsletter #12

Not a Lucid Web3 Dream Anymore: x402, ERC-8004, A2A, and The Next Wave of AI Commerce

Vocabulary for this article

Foreword

The End of One-Sized-Fits-All Prompts: Why LLM Models Are No Longer Interchangeable

JC-AI Newsletter #11

JC-AI Newsletter #10

JC-AI Newsletter #9

A Guide to SonarQube MCP Server on IntelliJ

JC-AI Newsletter: Easy Access to Expanding Challenges

JC-AI Newsletter #8

7 habits of Highly Effective Java Coding

From AI User to AI Pro

JC-AI Newsletter #5

Fourteen days have passed, and it is time to present a fresh collection of readings that could influence developments in the field of artificial intelligence.

JC-AI Newsletter #4

JC-AI Newsletter #3

New Java Benchmark for Coding LLMs puts GPT-5 at the top

JC-AI Newsletter #2

I n the first newsletter , we introduced a 14-day cadence, which means that this week it’s time for a new collection of articles from the fields of AI, LLM, Java and more.

article: OpenAI CEO Sam Altman warns of an AI ‘fraud crisis’

AI Newsletter #1