It’s so painful to read the LLM-compressed explanations. I can’t exactly identify what it is, but it’s an immediate tell and literally requires twice the effort to comprehend.

For example:

> Honest caveat, visible in the clip: the pxpipe arm answered the count first and needed one follow-up nudge to also print the ledger balance in the requested one-line format; the plain arm followed the format on the first try. Legibility is solved on Fable — single-reply format compliance is the remaining rough edge.

If I reread this four times, I can sort of interpolate what happened, but it’s mostly pointless and confusing information.

In my experience all models do this to an extent, but Claude seems to be the worst at this. GPT 5.5 is a bit more terse but seems to compress more valuable information.

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Yokohiii 4 hours ago | parent | next [-]

My thought on this is that LLMs probably mimic writing patterns and structures from quality resources. But they don't construct a plausible thought hierarchy like an average human does, so their train of thought turns into a rollercoaster of thought. So the order of information is for humans completely out of order.

My guess is that it's a known problem, which steered the frontier models into bullet point preference.

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adam_arthur an hour ago | parent | prev | next [-]

It's about information density.

Most LLMs by default seem to write both text and code with low information density.

You can kind of get around it by prompting them to optimize for compactness, but most just let it run with a more generic prompt.

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quantummagic 4 hours ago | parent | prev | next [-]

Here's one rewrite that would have helped:

To be fair, as you can see in the clip, the two models handled the prompt slightly differently. The pxpipe variant gave the right count initially but needed a quick follow-up to output the ledger balance in a single line. The standard model, on the other hand, nailed the formatting on its first try. We've completely solved readability here on Fable; our only real hurdle left is getting the models to follow formatting constraints perfectly on the very first reply.

Of course, this was just rewritten by another LLM.

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sebmellen 2 hours ago | parent | next [-]

Yeah, but as you say, this is another LLM rewriting it. The amount of noncontextual information is nauseating and destroys the point of a README (in my humble opinion).

A human might have written a disclaimer like this:

> When not using Fable, pxpipe may require additional follow-ups to precisely follow your formatting instructions.

This kind of garbled information dump is very inconsiderate of the reader, and all good writing is considerate of the audience consuming it.

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quantummagic an hour ago | parent [-]

To be fair to the rewriting LLM, it was given only that single paragraph, with no other context and asked only to make it more comprehensible. But your point still stands. Here's what it said about _your_ rewrite:

That human rewrite is excellent. It ruthlessly cuts out the "narrative" of the test case (the transaction counts, the video clip, the "first try vs second try" details) and extracts the only piece of information an actual user reading a README cares about: what to expect when using the software.

Which suggests some ideas that should have been included in the prompt, to get closer to your ideal rewrite.

	▲	rtgfhyuj an hour ago \| parent [-]
		[dead]

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georgemcbay 4 hours ago | parent | prev [-]

Reads a little bit better, but still reads like a writer getting paid by the word, which I guess is fitting.

	▲	cwmoore 3 hours ago \| parent [-]
		Or maybe: like a copywriter, paid by the dopamine hit

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hashmap 5 hours ago | parent | prev | next [-]

the foamy hedging makes me ill and hurts my eyes

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4 hours ago | parent | prev | next [-]

[deleted]

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lubujackson 2 hours ago | parent | prev [-]

[dead]