> When I send somebody a document that whiffs of LLM, I’m only demonstrating that the LLM produced something approximating what others want to hear. I’m not showing that I contended with the ideas.

This eloquently states the problem with sending LLM content to other people: As soon as they catch on that you're giving them LLM writing, it changes the dynamic of the relationship entirely. Now you're not asking them to review your ideas or code, you're asking them to review some output you got from an LLM.

The worst LLM offenders in the workplace are the people who take tickets, have Claude do the ticket, push the PR, and then go idle while they expect other people to review the work. I've had to have a few uncomfortable conversations where I explain to people that it's their job to review their own submissions before submitting them. It's something that should be obvious, but the magic of seeing an LLM produce code that passes tests or writing that looks like it agrees with the prompt you wrote does something to some people's brains.

The title and of this article is Don't Let AI Write For You, when its point seems to be closer to Don't Let AI Think For You (see "Thinking").

This distinction is important, because (1) writing is not the only way to faciliate thinking, and (2) writing is not neccessarily even the best way to facilitate thinking. It's definitely not the best way (a) for everyone, (b) in every situation.

Audio can be a great way to capture ideas and thought processes. Rod Serling wrote predominantly through dictation. Mark Twain wrote most of his of his autobiography by dictation. Mark Duplass on The Talking Draft Method (1m): https://www.youtube.com/watch?v=UsV-3wel7k4

This can work especially well for people who are distracted by form and "writing correctly" too early in the process, for people who are intimidated by blank pages, for non-neurotypical people, etc. Self-recording is a great way to set all of those artifacts of the medium aside and capture what you want to say.

From there, you can (and should) leverage AI for transcripts, light transcript cleanups, grammar checks, etc.

I've long considered writing to be the "last step in thinking". I can't tell you how many times an idea, that was crystal clear in my mind, fell apart the moment I started writing and I realize there were major contradictions I needed to resolve. Likewise I also have numerous times where writing about something loosely and casually revealed to me something that fundamentally changed how I viewed a topic and really consolidated my thinking.

However, there is a lot of writing that is basically just an old school from of context engineering. While I would love to think that a PRD is a place to think through ideas, I think many of us have encountered situations, pre-AI, where PRDs were basically context dumps without any real planning or thought.

For these cases, I think we should just drop the premise altogether that you're writing. If you need to write a proposal for something as a matter of ritual, give it AI. If you're documenting a feature to remember context only (and not really explain the larger abstract principles driving it), it's better created as context for an LLM to consume.

Not long ago my engineering team was trying to enforce writing release notes so people could be aware of breaking changes, then people groaned at the idea of having to read this. The obvious best solution is to have your agent write release notes for your agent in the future to have context. No more tedious writing or reading, but also no missing context.

I think it's going to be awhile before the full impact of AI really works it's way through how we work. In the mean time we'll continue to have AI written content fed back into AI and then sent back to someone else (when this could all be a more optimized, closed loop).

I agree with most of this, but my one qualm is the notion that LLMs "are particularly good at generating ideas."

It's fair enough that you can discard any bad ideas they generate. But by design, the recommendations will be average, bland, mainstream, and mostly devoid of nuance. I wouldn't encourage anyone to use LLMs to generate ideas if you're trying to create interesting or novel ideas.

I feel like LLMs are just forcing me to realize what writing actually is. For me, writing is basically a mental cache clear. I write things down so I can process them fully and then safely forget them.

If I let an LLM generate the text, that cognitive resolution never happens. I can't offload a thought i haven't actually formed - hence am troubld to safely forget about it.

Using AI for that is like hiring someone to lift weights for you and expecting to get stronger (I remember Slavoj Žižek equating it to a mechanical lovemaking in his recent talk somewhere).

The real trap isn't that we/writers willbe replaced; it's that we'll read the eloquent output of a model and quietly trick ourselves into believing we possess the deep comprehension it just spit out.

It reminds me of the shift from painting to photography. We thought the point of painting was to perfectly replicate reality, right up until the camera automated it. That stripped away the illusion and revealed what the art was actually for.

If the goal is just to pump out boilerplate, sure, let AIdo it. But if the goal is to figure out what I actually think, I still have to do the tedious, frustrating work of writing it out myself .