If someone asked me to set up a team in charge of software documentation, I would not hire for specific roles or cookie-cut job descriptions. Professions tied to knowledge buckets are bound to shrink or disappear. Instead, I would hire people that could move freely between four quadrants, each defined by the proximity to a focus pole and its skills. The poles in this team setup would be the following: Product Vision, Knowledge Design, Engineering Depth, and Delivery Strategy.

Not a month goes by without someone claiming they’ve killed tech writing. A few weeks ago, it was CodeWiki and its docs theatre. Now it’s the turn of Claude Skills and their ecosystem of Markdown instructions served as if they were executable code or macros. Docs, though, are tougher than they’d expect, because they’re the strongest signals in a sea of noise, and because they’re pretty much everywhere. Including, well, skills.

At the end of The writing was always the cheap part, I alluded to the fact that tech writers need to pick up new habits and skills, but didn’t dig into what that entails. These days, any LLM can put together plausible docs with some context and a simple prompt. So what is it that a tech writer should be learning now? Despite the fact that the AI landscape is ever shifting under our feet, I should be able to give you some actionable directions. Buckle up.

Last December, quite unrealistically, I took a solemn oath: I would not write again about AI for at least another year. I was growing tired with the incessant noise, the lack of stability, and the self-imposed stress of keeping up with all the attention we must spend on factoids such as how well an LLM can draw a pelican riding a bike, which bury the important aspects of our craft as if they were mere prompt flourish. With my passionate epistle, I thought I’d said all I had to say. I was wrong.

I like cooking recipes. They’re clean, serene documents where, at some point, one or more utensils enter the stage to perform a task. If you were to write one on how to use AI to augment your work as a technical writer, though, you would have a hard time deciding when and where LLMs come out of the toolbox to aid you. The variety of flavors in which AI presents itself doesn’t help. This is why I’ve come up with a framework that describes applications of the different AI tools at our disposal.

Hey you,

Yes, you, who are thinking about not hiring a technical writer this year or, worse, erased one or more technical writing positions last year because of AI. You, who are buying into the promise of docs entirely authored by LLMs without expert oversight or guidance. You, who unloaded the weight of docs on your devs’ shoulders, as if it was a trivial chore.

You are making a big mistake. But you can still undo the damage.

I never posted so much as in 2025. Instead of analyzing my own blog production, I chose to interview Claude Opus 4.5 and Gemini Pro 3 about it and get their predictions for next year (with a surprise guest). They never said “You’re absolutely right”, which is reassuring. They were also quite humorous at times. I had a blast co-writing this with them.

Instead of writing my tech comms predictions for next year like I did in 2024, I’ve written a fictionalized account of my day as a technical writer in 2030. It’ll be interesting to see whether we get there or not. Take it as a window into a possible future, one where AI usage is safer, more regulated, and better integrated with our workflows (as it should be).

Code Wiki, a new AI tool by Google, claims to generate a complete set of docs, including diagrams, from code repos. The landing page goes as far as saying “Stop documenting. No more stale docs. Ever”, a claim that made me stagger and reach for the nearest chair.

That these tools are laughably bad isn’t reassuring; their emergence hints at a deeper and more unsettling cultural problem.

The dam of AI-written doc contributions might be about to break. It’s already cracking for code, with posts wondering how to review a vibe-coded pull request consisting of nine thousand new lines of code. In the midst of what Tom Johnson describes as acceleration, docs-as-code writers wonder how to contain the seemingly inescapable wave that could bury their backlogs in AI slop. The answer could lie in taking a stance. This means crafting an AI policy for docs.