AI

I create a lot of content with audio. Interviews that become final podcasts, final podcasts, videos, and more. In almost all cases, a transcript of that audio is useful. Often, I use it to create a blog post based on that audio, and I am also in the process of creating interactive transcripts for my backlog of podcasts. And that aside, accompanying transcriptions of shows are good for SEO and accessibility.

JetBrains is known for its variety of developer-focused IDEs, all based around its IntelliJ core. In recent years, they developed their own writer-focussed plugin, Grazie, for handling grammar and style guidance, Writerside for a wide variety of tech writing tasks, and more recently, an AI assistant for writers. The company has also helped with community-maintained plugins such as those for markdown and asciidoc. But then, a year or so ago, JetBrains announced that Writerside would become a fully-fledged tech writing IDE. I've been using it on and off for some time, and in this post, I take a look at some of its features, recent updates, and related plugins.

Who do you think reads most of your technical writing? Customers? Potential customers?

API documentation is generally predictable, follows common patterns, and is one of the least interesting tasks in a documentation project. It's also a task with a degree of pre-existing automatic generation tools and practices. It sounds like a perfect use case for AI-assistive tools! In this post, I look at general and specialized tools for generating API documentation from code and text-based prompts. I also cover potential problems and pitfalls in generated docs and how to test the generated output to ensure its accuracy.

On May 23rd 2025, the MySQL database celebrated its 30th anniversary. Look at the usage trends for databases on DB-engine and MySQL and its owner since 2010, Oracle's own product occupy the top two spots. However, the same rankings show that the popularity of most of the top four is declining, especially for MySQL. It has been in slow decline since the era of "cloud computing" began, but like many other areas of technology, it is the demands of and for artificial intelligence (AI) that are causing the most pressure. As it celebrates its 30th year, what is the project doing to remain relevant and competitive in the new AI age? With rivals hot on its tail and some of its biggest competitors offering fully compatible, free alternatives, how does it plan to survive for another 30 years?