As someone with ADHD, you might occasionally find yourself staring at a sink full of dishes, thinking, I should write a novel, only to end up three hours later knee-deep in a YouTube rabbit hole about how ancient Romans made concrete.

It's not your fault; it's just how your brain throws a party. Enter Large Language Models (LLMs)—AI-powered helpers that might not do the dishes for you, but they can remind you to do them without judgment.

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Why LLMs Are Helpful For Folks With ADHD

In his article, "How Large Language Models Can Assist People with ADHD," Ed Finkler (aka Funkatron) — a passionate advocated for mental health in the tech industry — makes a strong case for why LLMs are a godsend for the easily distracted among us.

These digital assistants don't just provide helpful nudges; they can structure your day, break tasks into bite-sized chunks, and even politely rephrase that borderline-angry email you were about to send your landlord.

They're like the friend who gently pulls you back from the edge—except they're available at 3 a.m. and don't expect you to split the check.

But let's not get carried away. Yank points out that LLMs are not a replacement for your therapist, doctor, or the miracle drug that finally got you to return those overdue 📗 library books. 🤣 They're just here to help you work with your ADHD, not fix it. Think of them as a friendly sous-chef in the kitchen of your life—just don't let them take over the whole recipe.

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I’ve been volunteering at our local elementary school in the school library. This week, the creative head librarian held a “book tasting party” where she placed books of different genres at six different tables and had class groups rotate from table to table to “taste” each type of book. From horror to graphic novels, there was a book genre for many tastes.

Photo by Pritesh Sudra on Unsplash

Imagine if you could have a “flight” of docs sites to have a docs site tasting party! The docs aficionado in me wants to go to such a party. What would be served? How about a taste of Sphinx, Astro, Hugo, and Jekyll, with a final taste of Mkdocs and Docusaurus? Let’s have fun with it (even if the metaphor breaks down quickly).

Sphinx: The Rich Espresso for Documentation

Sphinx is a powerful documentation generator initially created for Python projects. It excels at producing structured, text-heavy documentation emphasizing cross-referencing and indexing. Using reStructuredText as its markup language, Sphinx offers robust extensibility through various plugins and themes. Many technical documentation teams appreciate its ability to generate outputs in multiple formats, including HTML and PDF. However, its complexity can be daunting for newcomers unfamiliar with its syntax or configuration.

Astro: The Sparkling Citrus Spritz of Static Sites

Astro is a modern static site generator designed for speed and flexibility. Unlike traditional SSGs, Astro allows developers to mix and match different frontend frameworks like React, Vue, and Svelte while focusing on shipping minimal JavaScript to the browser. This approach makes Astro an excellent choice for performance-conscious documentation sites. With its component-driven architecture, Astro enables content creators to build engaging doc experiences while maintaining simplicity in content management.

Hugo: The Smooth Bourbon of Speedy Site Generation

Hugo is one of the fastest static site generators available, and it is known for its speed and efficiency. Written in Go, Hugo boasts nearly instant build times, making it a favorite among developers who need quick iterations. It uses Markdown for content and has a powerful and flexible templating system. Hugo is ideal for large-scale documentation sites, thanks to its excellent support for taxonomies, multilingual content, and customizable themes. However, the learning curve can be steep for those unfamiliar with its templating language.

Jekyll: The Classic Red Wine of Static Sites

Jekyll is a well-established static site generator that powers GitHub Pages, making it a popular choice for open-source projects. Built with Ruby, Jekyll processes Markdown files and converts them into static HTML. Its simplicity and deep integration with GitHub make it an appealing option for developers looking for an easy way to deploy documentation. While Jekyll offers plugins and themes, its speed and flexibility may not match newer SSGs like Hugo or Astro. Still, it remains a reliable choice for lightweight and version-controlled docs sites.

MkDocs: The Refreshing Iced Tea of Documentation

MkDocs is a straightforward static site generator designed explicitly for documentation projects. It prioritizes ease of use with a simple configuration file and Markdown-based content. MkDocs includes a built-in live preview server, making it easy to see changes as you write. One of its most popular themes, Material for MkDocs, enhances the experience with modern styling and extra features. While MkDocs may not be as extensible as Sphinx, it is an excellent choice for teams looking for a quick, efficient way to publish documentation.

Docusaurus: The Trendy Matcha Latte of Docs

Docusaurus, developed by Facebook, is a React-based static site generator optimized for documentation sites. It provides out-of-the-box support for versioning, internationalization, and a structured navigation system. Docusaurus embraces a modern development approach, allowing developers to leverage React components for interactive documentation. Its ecosystem includes a vibrant community and a growing number of plugins. While its reliance on JavaScript may be a drawback for those seeking pure static solutions, Docusaurus remains a top contender for teams wanting a dynamic, developer-friendly documentation site.

Generative AI search engines are here, and they're about to flip the world of technical documentation on its head. These tools won't just tweak how we create, find, or read tech content in the next ten years—they'll completely reshape it.

Let's take a look at what's coming and how it's going to shake things up.

Search That "Gets You"

Generative AI search engines are kicking keyword searches to the curb. Instead of wading through endless links, you'll get straight-up answers that match what you're asking. For this to work, documentation teams must rethink their content—making it clear, bite-sized, and easy for AI to identify, understand, and digest.

Imagine a developer hits an authentication error in API version 2.0. Instead of pulling their hair out while searching, they ask, "How do I fix this error in version 2.0?" Boom—AI answers are delivered on a silver platter, pulled from release notes, FAQs, and code examples. No rabbit holes. No swearing at the screen. Just the right info, right when and where you need it.

The Death Of The Keyboard: The Future Is Conversational

And let’s talk about how all this is changing the way we interact with tech. Generative AI is rewriting the rules for keyboards and typing, making them feel like yesterday's tech.

Why type out awkward, choppy keywords like "fix API error v2" when you can say, "How do I fix this API authentication error in version 2.0?" AI loves a good conversation. It can turn searches into natural, intuitive chats instead of a guessing game with keywords.

Voice input is stepping in as the new favorite.

Why Type When You Can Ask Alexa Or Siri To Figure It Out?

And for the times when typing is still necessary, AI shortens the back-and-forth. It delivers straight answers, so you don't have to refine your search a dozen times. Plus, you can skip typing altogether with multimodal input on the rise. Upload a photo of an error message or tap on predictive suggestions, and AI will deliver the goods.

Sure, keyboards will stick around for professional work or those moments when voice input isn't ideal, but they're no longer the show's star. AI prioritizes ease and efficiency, letting us ditch clunky keyword searches for something that feels human. The future is conversational, and the keyboard is learning to share the spotlight.

Generative AI Search Engines Are Kicking Keyword Searches To The Curb

Early data from Microsoft Bing AI and Google Bard shows people love conversational AI that cuts to the chase with direct answers. Microsoft even bragged that over 100 million people started using Bing daily after they added AI—yes, Bing. Who saw that coming?

Read more

Circle April 7-9, 2025, in bold red marker because San Jose, California, is hosting ConVEx 2025.

This 27th annual confab gathers the sharpest minds in technical documentation, content strategy, content engineering, and content operations. Experts share tips, tricks, and secrets to creating, managing, and delivering better content.

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The Center for Information-Development Management (CIDM) delivers this annual event, seamlessly blending learning, networking, and inspiration.

Why You Should Be at ConVEx 2025

ConVEx packs a ton into two days. It's not just PowerPoint slides and coffee breaks.

Here's what's in store for attendees:

• Mind-Expanding Presentations: Industry experts will share tips, tricks, and tools you can actually use. Think strategies for tackling your biggest documentation headaches, not boring buzzwords.

• Panel Debates: Join smart people arguing (nicely) about how to fix content chaos, scale operations, and make self-service content less of a hot mess.

• Real-World Stories: Want proof that this stuff works? Case studies will show how top companies beat the odds, streamlined their processes, and made measurable progress.

Browse the Cool Tools Zone

Okay, it's officially called the exhibition area, but let's get real—it's like a candy store for tech doc geeks. Stroll through and check out the latest software, AI tools, and workflow hacks that will save you time, impress your boss, and maybe even make you look like a wizard at work.

Software and service vendors are ready to chat about everything from localization to automation. No awkward sales pitches—just helpful info, product demonstrations, and maybe some tasty chocolates.

Who Should Show Up?

If your job involves creating or managing technical product information or documentation content, this event practically calls your name. It's perfect for:

• Documentation Managers: You're tired of herding cats and need systems that work.

• Technical Writers: Learn tricks to improve your skills and avoid reinventing the wheel.

• Content Strategists: Get ideas for making content people want to use.

• Product Managers: Find out how great content makes customers happier (and your life easier).

• Customer Experience Pros: Find out how great content creates happy, loyal customers who spread the word about your offerings to others.

Why San Jose?

Because Silicon Valley, baby! It's tech central, and San Jose is where innovation, culture, and excellent tacos collide. You'll leave the conference buzzing with ideas—and maybe with a new favorite lunch spot.

Don't Sleep on This

ConVEx 2025 is your chance to meet like-minded pros, swap ideas, and learn from the best. You'll leave smarter, better connected, and armed with solutions to your toughest challenges. Don't miss it!

See the full agenda, speaker lineup, and registration details.

Pro tip: sign up early to lock in your spot. If you act quickly, you can save 10% off the cost of registration when you use discount code — TCW — at checkout.

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Let’s face it: as technical writers, some of us spend a inordinate of time staring at code blocks, inline commands, and system outputs. And when we’re not deciphering the latest JavaScript spaghetti, we’re formatting Markdown in Docs-as-Code workflows that feel like a modern-day version of the myth of Sisyphus.

Enter Monaspace fonts—a new type family that promises to make our lives easier and our documentation more readable.

Before you roll your eyes and mutter, “Another font?” let me explain why Monaspace isn’t just another fancy typeface. It’s a font system designed explicitly for technical content, and it might just make you fall in love with typography. Or at least tolerate it more.

What Are '“Monaspace” Fonts?

Monaspace is the Swiss Army knife of fonts: versatile, practical, and unexpectedly stylish. It’s a family of five distinct fonts—Neon, Argon, Xenon, Radon, and Krypton—each with its personality and purpose.

Think of them as your new best friends in technical writing, with features like seamless style mixing, texture healing (yes, that’s a thing), and metrics consistency.

Monospaced fonts (on the other hand) don’t play nice with others. Each has its own set of rules (metrics), so mixing them can introduce challenges.

Enter Monaspace Fonts — The Peacemakers of the Font World

Designers created monaspace fonts to mix and match without drama.

Want to add more personality to your code? Want to make it easier to process and understand? With monaspace fonts, you can build interfaces that bring order to the chaos and give your code the structure it deserves.

Monaspace empowers writers to juggle code, comments, and prose in the same document.

Why Should You Care?

Monaspace fonts address the common issue of monospaced fonts squishing letters together or spacing them awkwardly by using texture healing. This feature ensures uniform spacing and makes code blocks and inline snippets easier on the eyes.

Monaspace fonts also let you mix and match styles to convey meaning. Comments? Use a handwritten style. Auto-generated text? Try something bold. All without looking like a ransom note.

Monaspace’s flexibility isn’t just for show; the ability to mix styles helps your readers quickly differentiate between types of content, especially when syntax highlighting isn’t available.

Docs-as-Code workflows demand consistency across platforms, and Monaspace delivers. Whether your documentation is a PDF, HTML file, or printed user guide, Monaspace may help you ensure your content looks polished and professional everywhere.

I once thought structured content was the pinnacle of technical writing sophistication. Like labeling all your moving boxes and patting yourself on the back for being organized, I marveled at its clean tags and nested elements, smugly assured that everything was in its place. But just as you can’t solve life’s problems with a color-coded filing cabinet, I’ve come to realize that structured content, while essential, isn’t the whole story.

Welcome to the world of semantic structured content,
where you organize data to make it meaningful.

Structured Content: The Foundation

Structured content organizes information into a predictable framework using markup languages like Extensible Markup Language (XML) or its specialized cousin, the Darwin Information Typing Architecture (DITA). It locks in consistency, makes reuse a breeze, and lets you publish content across platforms and channels.

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Structured content has been a lifesaver for tech writers, rescuing us from the Wild West of unstructured documents and giving us scalable workflows instead of headaches.

But here's the rub: structured content, while fantastic for organizing information, doesn't know what it's talking about. It's like following a recipe exactly but not understanding why baking soda makes the cookies rise. Sure, it's got the structure down, but where's the meaning? Enter semantic content.

Semantic Content: Adding Meaning to Structure

Semantic content, the sophisticated older sibling of structured content, is the key to unlocking a deeper understanding. It doesn't just organize information; it explains what the content means and how it connects to other information. Using technologies like RDF or vocabularies like schema.org, semantic content enriches structured content with context and relationships that machines—and humans—can understand, enlightening readers and enhancing their knowledge.

Think of it like this: structured content is a beautifully organized cookbook written in XML. Semantic content is the same cookbook, but with notes in the metadata that say, "This recipe pairs perfectly with that one," or "Use this ingredient as a substitute in case of dietary restrictions." It's all about adding meaning to the structure, making the content more intelligent and thus more informative.

Here’s another example: a structured content model might include a product name, description, and specifications in a table. Semantic content, however, would go further by explicitly defining relationships, such as "Product X is compatible with Product Y" or "Specification A is required for Feature B." This added layer of meaning allows AI systems to draw inferences, answer nuanced questions, and create contextually-relevant connections that structured content alone cannot.

Why You Need Semantic Structured Content Now

You might think, "This sounds great, but do I need semantic content right now?" The answer is an unequivocal yes. AI and machine learning systems are rapidly becoming central to how people access information, and they thrive on context. They need content that doesn't just say, "Here's some data," but also explains, "Here's why this matters and how it connects to everything else."

For example, structured content can give users detailed specs and instructions if you write product documentation. Semantic content, however, can tell them how features relate, which configurations are compatible, and what scenarios call for specific actions. It helps AI systems answer complex user questions, create personalized recommendations, and support richer user experiences.

Without semantic content, your content is just an instruction manual;
with it, it becomes an intelligent assistant.

So, How Do You Get Started?

Transitioning from structured to semantic content might sound daunting, but it's more manageable than you think. Start by understanding the basics of semantic technologies like Resource Description Framework (RDF), JSON-LD, and Web Ontology Language (OWL).

Look at your content and identify key relationships—what connects to what, and how? Adopt semantic standards like schema.org or industry-specific vocabularies to ensure your content is machine-readable and interoperable.

Most importantly, you should collaborate with your team to weave semantic thinking into your content strategy.

The Natural Evolution of Technical Documentation

The shift from structured to semantic content represents a natural evolution in technical communication. As the demand for smarter systems and personalized user experiences grows, so does the need for content that not only organizes information but also makes it understandable to machines. By embracing semantic content, technical writers can not only meet today’s challenges but also help shape the future of intelligent communication systems.

Now is the time to lead this transformation.

Are you ready to make the shift? 🤠

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Ready to help shape the future of customer self-service? Heretto's groundbreaking research survey is back for its second year, and your voice is more crucial than ever.

The 2025 State of Customer Self-Service Survey goes beyond basic trends – we're uncovering the strategies that turn good support into exceptional customer experiences.

Whether you're crushing it at self-service or just getting started, your insights will help companies across industries unlock their full potential.

By participating, you'll:

• Get early access to industry-defining insights

• Help set new benchmarks for customer support excellence

• Join an exclusive community of forward-thinking professionals

Don't miss your chance to influence how businesses evolve their self-service strategies.

Take the survey!

Interested in the results from our previous survey? Grab your copy of the 2024 State of Customer Self-Service Report today!

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