I will share my experience, hopefully it answers some questions to tech writers.

I was terrible writer, but we had to write good docs and make it easy for our customers to integrate with our products. So, I prepared the context to our tech writers and they have created nice documentation pages.

The cycle was (reasonably takes 1 week, depending on tech writer workload):

    1. prepare context
    2. create ticket to tech writers, wait until they respond
    3. discuss messaging over the call
    4. couple days later I get first draft
    5. iterate on draft, then finally publish it

Today its different:

    1. I prepare all the context and style guide, then feed them into LLM.
    1.1. context is extracted directly from code by coding agents 
    2. I proofread it and 97% of cases accept it, because it follows the style guide and mostly transforms my context correctly into customer consumable content
    3. Done. less than 20 minutes

Tech writers were doing amazing job of course, but I can get 90-95% quality in 1% of the time spend for that work.

I’m on engineering side . We are in the same boat.

Writers become more productive = less writers needed not 0 but less.

That’s current step. Now if the promise of cursor that capable of Multi week system to be automated completely. All the internal docs become ai driven .

So only exception are external docs . But … if all software is written by machine there are no readers .

This obviously a vector not a current state :( very dark and gloom

"Productivity gains are real when you understand that augmentation is better than replacing humans..." Isn't this where the job losses happen? For example, previously you needed 5 tech writers but now you only need 4 to do the same work. Hopefully it just means that the 5th person finds more work to do, but it isn't clear to me that Jevons paradox kicks in for all cases.

Im not kidding when I say the tone feels AI generated.

It’s obviously not AI generated but I’m more speaking to the tonality of the latest gpt. It’s now extremely hard to tell the difference.

I agree with the core concern, but I think the right model is smaller, not zero. One or two strong technical writers using AI as a leverage tool can easily outperform a large writing team or pure AI output. The value is still in judgment, context, and asking the right questions. AI just accelerates the mechanics.

First, we've fallen into a nomenclature trap, as so-called "AI" has nothing to do with "intelligence." Even its creators admit this, hence the name "AGI," since the appropriate acronym has already been used.

But, when we use "AI" acronym, our brains still recognize "intelligence" attribute and tend to perceive LLMs as more powerful than they actually are.

Current models are like trained parrots that can draw colored blocks and insert them into the appropriate slots. Sure, much faster and with incomparably more data. But they're still parrots.

This story and the discussions remind me of reports and articles about the first computers. People were so impressed by the speed of their mathematical calculations that they called them "electronic brains" and considered, even feared, "robot intelligence."

Now we're so impressed by the speed of pattern matching that we called them "artificial intelligence," and we're back to where we are.

I think using AI for tech documentation is great for people who don't really give a shit about their tech documentation. If you were going to half-ass it anyway, you can save a lot of money half-assing it with AI.

It’s not so much that AI is replacing “tech writers”; with all due respect to the individuals in those roles, it was never a good title to identify as.

Technical writing is part of the job of software engineering. Just like “tester” or “DBA”, it was always going to go the way of the dodo.

If you’re a technical writer, now’s the time to reinvent yourself.

I remember the days when every large concern employed technical writers and didn't expect us programmers and engineers to write for the end users. But that stopped decades ago in most places at least as far as in house applications are concerned, long before AI could be used as an excuse for firing technical writers.

Documentation needs to be tested.

Someone has to turn off their brain completely and just follow the instructions as-is. Then log the locations where the documentation wasn't clear enough or assumed some knowledge that wasn't given in the docs.