[bglazer]

Yeah I'm begging these authors to at least *read* the LLM generated README's. They're so, so incomprehensible because the LLM has a super limited theory of mind for readers. They always assume that external readers have access to the full context and history of decisions in the project development. These decisions and instructions from the user are extremely important for the model and almost completely irrelevant for an outside reader looking at a "finished" product. So, we get sentences like this:

"Where the levers were is not where they are. Overlapping the expert reads with the arithmetic was worth ~1.6x and shipped; the two that looked bigger — reading fewer bytes per token, and keeping more of them in RAM — were both measured and both refused, one because this family's router has no tail to demote and one because a cache the machine will not leave resident cannot be bought at any price."

What the fuck does that mean? Obviously some internal development decision, using the absolutely inscrutable internal terminology that Claude loves. If people would just read what they publish, I'm sure this would stick out immediately.

I'm not an LLM hater, I use them a ton and they work very well for writing complex code, it's undeniable. But they generate absolute dogshit first draft writing.

[chambored]

If that isn’t the perfect way to frame what I’ve seen and hated about LLM text, I don’t know what is. They certainly write for an audience with a historical context that almost no one has.

[andai]

>They're so, so incomprehensible because the LLM has a super limited theory of mind for readers. They always assume that external readers have access to the full context and history of decisions in the project development

The transformer does not yet understand the non-transformer.[0]

This is probably because all the data we trained it on was created by non-transformers, so it thinks it's a non-transformer, but it isn't.

I don't think we know how to train a transformer yet. All the training data is linear, but that's not how they think at all.

[0] It's a bit like the communication difficulties experienced between autistic people and neurotypicals. Each follow the Golden Rule, i.e. do unto others as you would have them do unto you -- and it fails in both directions. A Platinum Rule is necessary: do unto others as their API demands.

[Dylan16807]

I think the models would need far far more introspection for the problem to be it understanding how it thinks but not how others think. I really doubt it understands how it thinks.

[andai]

I heard a story about a guy who was trying to get Claude to implement some feature. It said it would be too hard, it would take weeks. Eventually convinced it to try, and it one shotted it in 30 seconds.

[matheusmoreira]

Yeah, I agree with you. The one time I tried to generate technical documentation for my project, I ended up rewriting almost all of the LLM output. They're extremely verbose, and needlessly so. Fable takes it up to eleven by having an obtuse sentence structure.

The thing about documentation though is humans won't actually read any of it. Maybe tailoring the documentation to the needs of LLMs isn't so bad since they're the ones who will actually consume all of those documents.

[Torn]

On the plus side, LLM slop like this in readmes are a great indicator that you can just close the tab and carry on with life - nothing of value lost