AI;DR (AI; Didn't Read)

As to the first part, if you mean the demand side as in who wants to read slop LinkedIn posts, LLMs haven't changed the fundamental nature of that. It's always been awful. Therefore the point is who cares if an AI has written it. As I said, it's all pablum anyway. But I don't agree with how you are describing the problem. Most marketing or self promotion is "optional" then? Why is not having a direct buyer asking for the work equal to "volunteer" work? Anyone who has been around marketing knows conversion rates are incredibly low. That's just the nature of it. It still often makes sense from a ROI perspective. There are many if not most cases were > 99% of people might readily say "who asked for this?" and it will still make economic sense to convert the fraction of a percent.

I similarly don't think your second point makes much sense. I think people going on about writing or domain experience as a skill are missing the obvious writing on the wall. If you are not an exceptional writer you will be replaced. Most people will be replaced then. Or at the very least, their diminished market power is inevitable. The end state of these models is in my view clearly aligned to less human in the loop and more automated self prompting. Most people's prompts are not that unique. If someone has a superior prompt that eventually gets integrated into the model. Eventually the model learns to ask itself the superior question, even if the spark is a profoundly lazy human invocation. The progress along code generation is then joined hand in hand by progress to full automation. Why is generating a prompt harder to solve than generating code? Why will both not advance in the next decade? Suggesting code will be increasingly machine written while saying humans will still need to be around to write instructions just strikes me as denialism of the scale of the change. If you think that in 10 years most of the back and forth is not going to be LLMs talking entirely among themselves I think you are in for a rude awakening.

As I said earlier, if a human cares a human will author. As for the rest of it, it makes almost no difference. Bad, lazy writing has always existed. Why would I take solace that a human has produced slop over a machine? The question is not "do I like it" but "do I care". The answer is no. Most things in the economy I don't care for or like. But certain things are inevitable as humans conglomerate. A well organized mind learns to get over it. Quite frankly if LLMs push LinkedIn over the edge and lead to the destruction of that platform I would be pleased. It was always a center of corporate slop and backpatting, something that in theory was optional but was more like a mandatory career chore, a step in the middle to actual work. It just is kind of amusing that your example of why AI writing is bad is because it is ruining LinkedIn, as if that place wasn't always trash. It just makes my point. In domains were humans care about human authorship, it's just not an issue in the same way. I've never heard someone care about LinkedIns viability as an ecosystem from someone who didn't work there. If LLMs are making the site unusable they are doing God's work.

> Look, I get it. It’s Q3 2026, and we should expect that everyone is utilizing AI at SOME point in their process (sourcing ideas, creating outlines, refining prose, etc.)

How do people not realize how up their own @$$ they sound when they say things like this

Of all the things in this thread - this is the one that grinds my gears the most. Colleagues that believe it’s ok to reply with unedited garbage when you engage with them as a human.

I don’t think we need to write code anymore unless we want to - but we DO need to be humans, and respect the time of other people.

It’s not some conspiracy. If they knew how to make the AI responses better and more concise, they would. They just don’t yet.

This isn't just on code.

When I'm writing technical documentation, it keeps the explanations in. Same when writing non-technical documentation. When I was having it attempt to generate a Pathfinder 1e class for a Sword Dancer, it was leaving in notes about why it removes things I told it to remove/rework.

And it isn't just Claude. I've seen the same with GPT models, with Grok, with Deepseek. Each AI isn't quite the same with how it approaches this, but in every case they seem to have a strong bias to retaining information, even bad information that we want gone, so it is like they have a, dare I say, subconscious bias to retain the information. Putting a note in a comment or explaining why to not do something or something was undone is a good way to retain information while still achieving the goal (well, if you ignore the part about the human intention for the information to be gone).

This then weakens the AI in the future, as I find AI struggles with the more incorrect information. Sure, a comment saying "not X because Y" is less 'context damage' than a comment saying "X" (assuming X is wrong), but it is still a slight shift to X being present in context in some way. One off, AI's seem to perfectly handle this without issue. But after hundreds or thousands of cases build up? The attention mechanism seems unable to keep up and incorrect information flows it. This effectively creates a sort of vibe coding maximum size unless there is a human janitor cleaning up the bad information on the context stays nice and clean.

But this is all simply a feeling I get as I use AI to do different things and isn't at all backed up by any formal study.