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.

What, you don't like your caveats to be honest?

dead giveaway for me that something someone made and wants to share = they dont understand what they put together enough to like speak to it with some level of authority.

people can make some really useful stuff with AI especially when its a domain they're already an expert in, and it would go a long ways for them to just sit and explain that 1. they used AI to help 2. their own words to explain what the heck they put together, especially if they can speak to some of the limitations AI has working with it. just goes a long way to demonstrate this guys stuff is worth tinkering with because he has a good grasp on what was created

for 99% of the stuff out there now people are literally operating in domains they don't understand at all, i just close my tab when i see the damn vibe coded readmes