Java Web Development (JSP/Servlets) Services

If you've ever written raw JDBC, you know what's coming. Open a connection, create a PreparedStatement, set parameters by index (hope you counted right), iterate a ResultSet, close everything in a finally block, declare SQLException on every method signature… It's a lot of ceremony for "give me some rows."

I've been experimenting with Ujorm3, a new lightweight ORM library for Java 17+. Here's a realistic example — a JOIN query that maps results including a nested relation:

Apache Spark is one of the most powerful tools in the data and AI engineering world. It helps process massive datasets and is widely used across industries, irrespective of cloud platforms.

But when you move from learning Spark to running it in production, you start seeing real challenges.

Last week was about Metal and the Skin Designer. This week, the headline items are about what a brand new project looks like when you generate it: the default JDK is Java 17, and every generated project ships with an AGENTS.md authoring skill that lets any modern AI agent work on the project intelligently. 

There are also some other things worth covering: a runtime accent palette on the new native themes, three Metal follow-ups (one of which introduces a new matrix-correct translate API), the JDK 11+ String API gap closed, and iOS push permission that no longer fires at app launch.

It has been one of those weeks where the diff is bigger than the headline. The headline is short — Codename One now ships modern native themes: an iOS "liquid glass" look and an Android Material 3 look, bundled into the iOS and Android ports, on by default in the Playground, and selectable from a brand new menu in the simulator. The diff behind that headline is several thousand lines across the platform ports, the simulator, the GUI plumbing, and a small army of screenshot tests.

The theme behind the work is simple: Codename One should look modern out of the box on every platform we ship to, and it should feel fast. Almost everything in the past week of commits is in service of one of those two goals.

This post walks through building and running a real-world agentic workflow with Agentican and Quarkus. Specifically, an agentic workflow to automate market research and information sharing:

1. Identify the top vendors within a market category.
2. Research the positioning and strengths of each vendor.
3. Classify the findings as either standard or urgent.
4. Draft a brief to share with others in the company.

Prerequisites

• Quarkus
• Java 25
• Maven (or Gradle)
• LLM provider API key

Step 1: Add the dependency

Create a Quarkus app, and add the Agentican Quarkus runtime module: