How do you recognize someone as having true opinions and knowledge from someone having just appearance of them?

And there are countless other jobs out there where people are the “voice” of another party. From those who manage social media presence, to PR firms, to copyrighters, all who put statements out on others behalf.

There was already an industry of professionals whose job it was to have others write things on our behalf, and that existed long before LLMs were a thing. What LLMs did was make that that service available much more cheaply.

And then if you want to tell a message with a different tone, again, you must consider differently.

The considering can be strengthened with exercise.

I can't imagine worrying about signaling as I write: what a huge distraction.

The problem is: this type of thinking and writing takes a lot more time and attention.

How much consideration should you put into a message? It's a personal answer, but also one that can be constrained by time.

They can be broken and jumbled, or terse AF, or combine to be Pulitzer-quality prose. Either way: I want to consume their own unique human expression of a concept.

There's value in raw human expression, including in the missteps.

If I instead want the regurgitated waggyings of a bot, then: I know how to get that on my own.

We've all got web browsers and pocket supercomputers. We've all (well, most of us) been alive and aware of LLMs since their recent rise from infancy.

It's a no-brainer for us to paste some paragraphs into our favorite chatbot and get a summary or an artificial expansion or whatever else we wish to have. If that's what our goal is, then we can do that on a whim -- and we can still retain the original expression.

But doing it on our behalf is deleterious, unsettling, and unhelpful. It has negative value to the beholder.

Elsewhere it’s painful and irksome when you didn’t ask for it

The exercise of writing is an important step of actually understanding your own thoughts properly. Readers are reading to get a sense of your own experience and ideas on the topic, if it turns out you didn't actually write the final thing yourself they'll always feel a sense – in whatever way – of being conned by the author. Intentional or not.

Technical documentation, where what the reader wants to come away with is the clear facts on what something does and how to use it/whatever, is a different matter. But even then editing is key – overlong text, unnecessary information, these will again fight against what the reader is there to get.

With that said, if you do want to do it, a disclaimer is at least upfront and may well show there's no intentional attempt to deceive.

The other difference is that, if I get AI to write something for me, I expect something AI-written. If I am writing something for you, you expect something that I wrote, not something that AI wrote.

Running the code only confirms that it works with the precise input, in the precise environment, under the precise circumstances you run it under. It doesn’t ensure that the code is correct. Thinking through the code, on the other hand, lets you consider all possible cases. It’s the difference between experiment and (mathematical) proof.

For an objective correctness proof, using a formal language is indispensable.

Hard for me to imagine. You feel no pride in using a tool to accomplish a goal?

> Code has no such personality. I don't tie my identity or ego to code the same way I would an essay

Code certainly does have a personality. When working with teams for a while you can absolutely get a sense for which person wrote what code in a codebase, just by subtle little tells.

You may not tie your identity or ego to it, bully for you, but for me I take a lot of pride in writing clear and maintainable code that contributes to big projects in meaningful ways.

Maybe the problem with software is there's too many people who treat writing code as a mere means to an end, instead of a very important part of the process.

The danger for me in LLM code is the same as in writing, it's just that I'm not typically writing at the same scale as when I'm building something. The final piece when I'm writing is usually a message or a 1,000 word article at most. So I'm naturally going to analyze it quite intensely, because I can afford to. And I don't really use LLMs for this at all. I use them for things around writing (research, interrogating ideas, situationally specific stuff, mapping, visuals, publishing, etc.) And the code equivalent to an essay or message would probably be something like a single script, or the sort of thing I'd write as example code when I'm teaching. In those settings, again, LLMs can be helpful, but I'm still going to be really opinionated at a highly detailed resolution.

But a codebase is more comparable to a novel than an essay. Or more directly, the writing in a codebase is usually the documentation, which grows commensurately with the codebase. And the real LLM risk here is the drift that can happen over the course of many epics or "chapters" as the LLM writes "code that works but is imprecise and probably shouldn't work this way" or introduces weird new terminology that neither of us can precisely define. Worse, this usually becomes obvious down the line, and I have to parse through the verbose constructed world the agent has created to trace the issue back. That's a big cognitive tax, because I'm holding these weird parallel worlds of "How did the LLM's alien brain get here within the bounds of the contracts" and "What do I really want this to look like".

So I think it's fundamentally the same phenomenon, and we're all developing our skills around working with it in real time.