Vanilla Java

One of the first challenges developers might face is getting generative AI to produce accurate documentation. Once you are comfortable doing this, the next challenge is creating enough documentation to be helpful without overwhelming the reader. Until generative AI came along, it might have seemed like there could never be too much documentation. Now, the challenge is to provide just enough detail to give understanding without overwhelming the material with unnecessary details. I was exploring the best way to generate accurate documentation for a project as I was flying over Australia and saw Alice Springs on the map, and it reminded me of the Reverse Baltimore Phenomenon. Generating documentation can give a "sense of completeness" that will likely be a distraction rather than have practical value. The text produced by a generative AI system can superficially convincingly feel "whole", but much of it is fluff that isn’t actually helpful to the reader or an...

This article was AI-generated using this project as context. AIDE Project . The purpose of this project is to see how much an AI could generate given enough context, and in this project, all the "source" code is generated using the requirements and unit tests as context. This follows the Next-Level Development: Harnessing AI with AIDE approach. The main parts are: Requirements Documents in .adoc format. JUnit tests in Java. AIDE itself. AI-generated code in Java. Even the articles written about AIDE are part of the context for the AI. This article is about how to write requirements as a prompt for AI to generate code, seeded with AIDE in the context. Everything after this line is AI generated. Prompt engineering can differentiate between AI-driven code that works and genuinely excels. Drawing insights from real-world Java projects—especially those striving for low latency, high throughput, and clear domain logic—this article will show y...

If it’s worth doing by hand, it’s worth automating. Just because not everyone is (yet) a world-class developer; that doesn’t mean we can’t step closer to that expert-level space. In this post, I will introduce AIDE (Artifical Intelligence Development Environment), a powerful workflow that merges AI-driven code generation with a sharp focus on documentation-driven development. With AIDE, I tap into the best of artificial intelligence (AI) while respecting the real human insight needed for domain-specific logic. The result? An environment that streamlines repetitive coding, synchronises requirements, code, and tests, and elevates your engineering game. Here is a practical example of an AIDE on GitHub developed using it’s own AIDE. Introducing AIDE: Merging AI and Documentation-Driven Development AIDE transforms development by combining: Prompt Engineering with AsciiDoc : Clear, structured prompts guide AI to produce accurate, contex...

Introduction Java’s annotation system has come a long way since its introduction in Java 5. At first glance, annotations appear to be mere metadata markers on classes and methods. However, annotations can do much more than that. You can nest types within them, incorporate fields that reference helper classes, and even embed logic via static singletons. These capabilities provide a powerful mechanism for integrating domain-specific or framework-specific functionality right into your code, in ways that are both compact and self-documenting. Why Add Code to Annotations? The Java language specification usually treats annotations as static metadata describing a type, method, field, or parameter. However, you can leverage nested classes (including enums, interfaces, and even other annotations) to extend the functionality of a single annotation. This approach allows you to keep logic closely tied to the metadata, rather than scattering it across multiple classes. Common use ca...

I find time fascinating and surprisingly complex. Time zones and calendars change from place to place over time. There are a number of interesting websites on the subject. Time is one of those concepts that appears deceptively simple on the surface yet becomes increasingly intricate the more we examine it. As software developers, we often face scenarios where we must handle dates and times and their myriad associated rules—time zones, calendar systems, cultural conventions, and historical irregularities. Working with time can lead us into subtle pitfalls that affect everything from straightforward user interfaces to global financial systems. Time is an illusion. Lunchtime doubly so. — Douglas Adams The Hitchhiker’s Guide to the Galaxy The Surprising Complexity Behind Time Time is not uniform. Humans have invented calendar systems and measurement techniques, each influenced by politics, religion, and culture. As a result, how we record and interpret dates ha...