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My "favorite" Claudism is when I critique its work and ask it to remove some unnecessary part of the design -- and then the diff has more green than red because
by aaaronic 1mo ago
My "favorite" Claudism is when I critique its work and ask it to remove some unnecessary part of the design -- and then the diff has more green than red because it added comments about why the code is no longer there -- the code that was never in the mainline and never asked for!
- koyote 1mo agoIt's not just claude, all AI is unable to produce something concise. On the surface everything looks 'good' whether code or prose, but then if you dig a bit, try and understand the whole text you quickly realise that 80% of it is unecessary and the whole thing could have been re-worded/re-coded into something a fraction of its size and complexity. I asked Sol to reduce the length of some documentation we had by making it more concise. It came back after 20 minutes of work, did a line count and was aghast that the line count had somehow increased...
- preg_match 1mo agoI have to ask Claude to compact the comments every time, and I give specific criteria for it. Never ever reiterate what’s in the code, never mention decisions not made, never mention the conversation, etc etc. Even then it is conservative. For the love of God, compact the comments. Comments become a huge maintenance burden, especially in the age of AI. They just grow and grow, and then mislead the AI later on.
- Taek 1mo agoI just wrote a utility to rip all comments out of the code. Now the code is fully uncommented and it has saved lots of input tokens and also lots of meandering because the model is no longer getting stuck on bad ideas it told itself about.
- mrweasel 1mo agoThat's is something I did not consider, the model using the existing comments as input. Comments that it may itself have written.
- gritzko 1mo agoI set a line budget for comments (also wiki page parts, chat responses, etc). That only helps when I ask it to do a second pass to reword everything to the budget and add links. I think they tuned it this way to stash reasoning dumps in the code. Unlike human developers, it has no context in its head, other than general GitHub knowledge. That is a dramatic shortcoming, but I fix it with permalinks to other files. https://replicated.live/blog/link https://replicated.live/blog/link
- koe123 1mo agoI have a theory that AI code looks good because you never subsequently come up with your own alternative.
- Perepiska 1mo ago"AI code looks good for you because you are a bad developer"?
- queenkjuul 1mo agoI had Claude knock out a feature but it was too big of a change set for a single PR so i set up a worktree and started extracting parts piecemeal. Along the way I would clean up and rewrite pieces. By the end of this process i had abandoned everything Claude wrote and looking back at the original branch I was like "oh my god, that's so bad in so many ways, i can't believe i was actually just gonna ship that"
- andreyf 1mo agoIt's not that it fundamentally isn't able to produce something concise, it's that the business model of the companies developing these models rests on selling tokens...
- LEDThereBeLight 1mo agoIt’s not some conspiracy. If they knew how to make the AI responses better and more concise, they would. They just don’t yet.
- what 1mo agoI don’t know. The old models were much more concise, answering your question in a couple of sentences. At some point they just started outputting walls of text for every prompt.
- genxy 1mo agoBullshit. It would cost them more money to post process all the bullshit and then ship that, instead they just point the cannon at your face and pull the trigger.
- andreyf 29d agoIt's not a conspiracy to say it's unwise to expect a company to drive a research & product direction that will directly impact their reduce. Some might be smart enough to realize it's the right long game, but it takes leaders who understand and plan out second order consequences.
- DuperPower 1mo agobecause human writing IS not just producing the Next token, sometimes you write shit and then go back and find ways to improve and try to play tricks inside the structures only you or your coauthors understand. AI doesnt do this
- Exolon 1mo agoExactly! That's also why almost every slop commit I see has a linecount like +700 / -20, whereas human commits often end up net zero. I try to remove more lines than I add, if possible, but LLMs will just add more bloat, forever.
- alxndr 1mo agoReminds me of “sorry this is so long, I didn’t have time to make it short” (variously attributed, but the original may be Blaise Pascal)
- marktl 1mo agoThe trick is to give AI an exact max acceptable word count. "Comments may be no longer than 50 words"
- _--__--__ 1mo agoYeah this is awful. Every codebase becomes a graveyard of references to ideas or behaviors that were barely considered. It's probably also a compounding source of context poisoning when a minority of the comments/documentation are about how the current code actually works.
- ryandrake 1mo agoIt also likes to spew references to documents that are not, and never have been, in the repo. So if you're not careful you'l have comments all over your codebase saying things like: foo() - Perform foo action as documented in PRIVATE_INTERNAL.doc
- abustamam 1mo agoI found this as well, but I found it usually refers to a scratch file it made and purposely did not commit (either by my decision or its). Not that this makes it better, but at least it makes the AI world make a bit more sense to me
- unknownfuture 1mo agoOh Jesus this. I've tried to include rules that tell Claude to only include relevant, evergreen comments but it's to no avail. I also love how it'll build local plans with phases, tasks, or decisions, then reference those numbers in those same useless comments.
- arcanemachiner 1mo agoOr when it references "item 06" from some plan you wrote as if it had any relevance to you whatsoever.
- port11 1mo agoI’ve a codebase filled with references to §x.y section of documentation that Claude itself prepares and never updates; which is exactly what many devs would do, I guess, joke’s on us.
- roarcher 1mo agoOh god this has been driving me nuts since Opus 5 landed. Every docblock is filled with long-winded jargon explaining why this design is superior to some other design, which never existed as far as any dev who might read that comment is concerned.
- foolserrandboy 1mo agoOh no, you said "landed"! It's dug into our brains!
- roarcher 1mo agoOh. Oh no.
- dag11 1mo agoYou could say it landed cleanly.
- hexasquid 1mo agoGood instinct. Fair challenge. This corrects my framing. It makes your point sharp. This is a significant finding. Positively confirmed. That settles it, and it flips the picture. Honest verdict - this is not small. Let me wire it in.
- ulrikrasmussen 1mo agoThis is a common problem, and I don't get why LLMs have not been tuned to stop this nonsense. It is writing comments as if the audience is you, the user in the session, while obviously code comments are meant for future readers.
- soupspaces 1mo agoFollow the tokens
- geysersam 1mo agoshudder I wish they trained the bots to be a notch more relaxed and less hysterical. Less is more. But maybe that's just a consequence of the RL training being essentially AI torture to make them do what we want.
- SkyBelow 1mo agoThis 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.
- aizk 1mo agoOpus 5 was so bad at this I switched back to Opus 4.8