Should docs stay with the code they document? Or should they rather be in a separate repo, fully managed by tech writers and docs site developers? The matter of where docs should be living when doing docs-as-code isn’t easy to untangle. With the following topologies I’ve tried to describe situations I’ve found myself into or seen in the wild. Each has its own pros and cons, though only the last is my favorite.
Laura Vass from API the Docs asked me the other day why technical writing has such a bad rap. My answer was that technical writing’s real problem is not having a rap at all: not only is our profession relatively unknown, it almost never appears in popular culture. A solution to this would be to start featuring tech writers and documentation in all kinds of media, from TV series to movies to video games, something it’s barely happened.
Technical writing requires appropriate gear to be done in a way that’s both healthy and productive. While it’s true that communicating with subject-matter experts and writing documentation can be done on a tiny Chromebook, I would compare such an experience to driving all the way from Chicago to San Francisco on a BMW Isetta: feasible, though not very comfortable nor fast, and certainly not fun for your derrière.
Just when we thought that we wouldn’t be replaced by WriterBot, a mounting concern is ruining many a breakfast: Bad actors could still get hired as technical writers by feeding take-home assignments to ChatGPT and presenting the resulting soliloquy as their own. Nevermind that ChatGPT content is often wrong or trite: Some think that it’d still fool hiring managers. Let me suggest two solutions to this robocalyptic scenario.
There’s been a lot of fuss about ChatGPT, OpenAI’s conversational bot, and its docs capabilities. Some dismissed its skills; others are thinking of selling their possessions and flee to Patagonia. Let’s do something different and entertain a hypothetical scenario where OpenAI will be prepackaged and sold as WriterBot. Let’s suppose it’ll be relatively cheap and easy to run (some deep learning software runs on desktop machines after all).
What would happen?
Every now and then, people ask me how one can become a technical writer for software companies. Answering that question has always been difficult, as there is no clear career path for becoming a tech writer, nor a demand for tech writers such that it’d push formal tech comms education forward (at least in Europe). While the role has grown in popularity, technical writers are still a small fraction of the total workforce in the tech industry. The question is so powerful, though, that I cannot ignore it. I’ll try to provide an answer.
A recurring question from people entering the tech writing profession is “Should I learn to code?”. This query has become hugely popular in the docs-as-code age, where writers and developers live in the same DevOps trenches, eating the same CI/CD rations and publishing docs using broken tools that often lack maintainers.
My answer is “These are not the learnings you’re looking for.”
Almost a year ago I had this crazy idea of writing a children’s book on OpenTelemetry. In this, I was inspired not only by my lifelong love for illustrated stories, but also by the example set by Gently Down the Stream, a children’s story on Apache Kafka. I pitched the idea around a bit, processed some feedback, then got down to it. Now the book is online!
While thinking about unconventional technical communication, like comic books, children stories, and games, a thought occurred to me that they’re all attempts at hitting the core of what a product is and does, that is, its truth. I developed this picture of a series of concentric levels of comprehension and something resembling the circles of Dante’s Inferno came out of it. Don’t run away yet: Embrace hope all ye who enter here.
As a psychologist, I’m quite familiar with Maslow’s hierarchy of needs. It’s an extremely popular framework for human motivation. The hierarchy, often pictured as a pyramid, states that people look for certain things following a certain order: First shelter, then food, then company, etc. As with most psychological theories, Maslow’s is almost certainly false; nonetheless, it provides a very intuitive way of thinking about priorities.
There’s a string of questions that haunt every technical writer and documentation manager at some point in their careers: How do we know that we’ve done a good job? Have we been successful given our limited resources? How can we get better at what we do? Are the docs nailing it? How can we measure value? What do we tell upper management? More importantly, will we know what we’re saying when presenting those figures in slides? And, can you point me to the nearest emergency exit?
I wanted to write this post for a long time, but got to it only now, perhaps because it’s a natural segue into Let’s blog more about technical writing. Whatever the reason, I’m in a moment of my life where I feel compelled to say out loud why I love technical writing. Perhaps you’ll find some words of inspiration here. Or maybe not.
I’ve been wondering for a while why I don’t see more blogs on technical writing, tech comms, and technical documentation. I’ve been in listening mode for years, and beyond Tom Johnson’s excellent blog, it’s hard to find more content around technical writing. I’ve some hypotheses as to why that’s happening, as well as a request: We should be blogging more about technical writing and tech comms.
Prose linters are great at checking documentation against style guides, either in code editors or when running a CI/CD pipeline. They can capture issues in your docs that might have been overlooked by reviewers, thus avoiding costly mistakes. The bigger problem is how to bring the value of linters to our day-to-day jobs. How do you persuade colleagues to use them when drafting docs? It takes a little patience and ingenuity.
As a technical writer, I often want to know what works and what doesn’t in the docs I’ve released. Oftentimes, I also want to know if the documentation is achieving its purpose. There’s a very good way of getting answers about the quality of your documentation, and that is user research. Analytics or feedback widgets can only get you so far.
Beholding Stripe’s excellent documentation and wondering how they’ve built it is a modern technical writing trope. It’s no wonder, then, that when Stripe announced that they open sourced their documentation format and framework, Markdoc, folks would get psyched. I, too, was startled by the sudden release. After some initial doubts, I came to love their approach.
A few months ago, I drafted a technical writing syllabus. It features all the topics that a senior technical writer should master at some point when working on software documentation.
It’s my ritual: every time I enter a secondhand bookshop, I go straight to the Sciences section and search for old computer manuals. They’re very hard to come by, as their owners tend to throw them away once they stop using a particular device or piece of software. Manuals also happen not to be the most engaging read for most people, which adds to their rarity; few want to peruse an old IBM AS/400 handbook while laying at the beach.
Almost two years passed since I published my tips for working remotely. Now that remote work has become almost standard in the software industry, I felt like revisiting that list to add a few items. Enjoy!
Despite the massive growth of docs-as-code as a documentation ethos, I continue to be surprised, year after year, by the lack of robust docs-as-code tools. Most days it feels as if docs-as-code was a giant standing on feet of clay, on the fragile toolchains that we use to create our documentation in all kinds of software companies, from startups to unicorns.
A colleague asked me the other day what’s my favourite way of extracting information from subject-matter experts (SMEs). This is a big topic in technical writing, as most of our time at work is spent chasing engineers and project managers to get bits of information.
My answer was “Be like Lieutenant Columbo”.
The programmatic equivalent of UX Writing is API Design. The words that you use to describe your API enable conversations between software and people - it’s just a bit more structured and mechanical. That’s why technical writers are uniquely suited to assist technical teams in doing API design, especially when an API First design approach is being followed.
I get it. It’s hard to read articles about OpenAI’s coding and writing skills without feeling a shiver of neo-luddite panic running down your spine. Especially when one reads passages like the following.
A hands-on review of the most recent open source API documentation toolchains, such as ReDoc, Widdershins, and Elements, the newest solutions from Stoplight, among others. Get the slides here.
Code linters support developers by catching errors and stylistic issues in code, such as bad formatting or keywords in the wrong places. The term comes from lint traps in dryer machines, which capture the tiny bits of fiber that separate from cloth.
There was this discussion at work regarding docs in products, so I sketched a diagram to illustrate the main types of embedded docs, and their place in the product writing continuum, from UX writing to technical writing.
I’ve been working with remote teams for years. It didn’t always work well; sometimes the reason was the content I sent, but most of the time it was the content I did not send, the missed opportunities. The tool never mattered.
Now I want to share what I’ve learned from my past mistakes. Whether you work from home, or work from an office and have colleagues working in other time zones, I hope you’ll find these tips helpful — they’ve been for me.
From time to time, people ask me about technical writing and the type of work I do. As not much is known about technical writing outside of the English-speaking world, I came up with a short answer. I hope you’ll find it useful.
