this post was submitted on 29 Mar 2026
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The post Xitter web has spawned so many “esoteric” right wing freaks, but there’s no appropriate sneer-space for them. I’m talking redscare-ish, reality challenged “culture critics” who write about everything but understand nothing. I’m talking about reply-guys who make the same 6 tweets about the same 3 subjects. They’re inescapable at this point, yet I don’t see them mocked (as much as they should be)

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[–] fiat_lux@lemmy.world 5 points 1 day ago* (last edited 1 day ago) (1 children)

That was great, thank you! Full respect to this absolute maniac for tracing some of the spaghetti, I was definitely not going to try that on my phone.

They've validated most gut feelings I had about how Claude works (and doesn't), based on my experience having to use it. I'm feeling pretty smug that my hunches now have definitive code attributions.

But the one unfortunate part about all of this is that this leak and the ensuing justified sneers about specific bits are going to be fed back in to their codebase to fix some of the gaping holes. It's an embarrassing indictment of the product, but it's also free pre-IPO pentesting. Sort of like their open source pull request slop spam "undercover mode" was probably used as a way to extract free labor in the form of reviews from actually competent developers. This doesn't seem as planned though.

[–] blakestacey@awful.systems 4 points 1 day ago (1 children)

In practical terms, what can they do? Add instructions to say "You will not generate spaghetti code that will humilate us when real programmers see it?" Perhaps in all caps?

This is what theirnorganizarion is capable, after tremendous expense, of producing. I don't think that bodes well for their prospects of improvement.

[–] fiat_lux@lemmy.world 2 points 21 hours ago (1 children)

Sorry, this was more of a rant than I thought it would be, I hit one of my own nerves while writing it. This is what happens when you're not in a good position to escape enforced AI usage hell. Tl;dr in bold at end.


wall divider


I can think of several practical measures, because I've tried them myself in an effort to make my coerced work with LLMs less painful, and because in the process I've previously fallen into the gambling trap Johnny outlined.

The less novel things I tried are things they've half-assed themselves as "features" already. For example, Johnny found one of the things I had spotted in the wild a while back - the "system_reminder" injection. This periodically injects a small line into the logs in an effort to keep it within the context window. In my case, I tried the same thing with a line that summed up to "reread the original fucking context and assess whether the changes make a shred of sense against the task because what the fuck". I had tried this unsuccessfully because I had no way to realistically enforce it within their system, and they recently included the "team lead" skill which (I rightly assumed) tries to do exactly the same thing. The implementation suggests they will only have been marginally more successful than my attempt, it didn't look like they tried very hard. This could be better implemented and extended to even a little more than "read original context".

For this leak, some of the very easy things they could have done was to verify their own code against best practises, implement the most basic of tests, or attempt to measure the consistency of their implementation. Source maps in production is a ridiculously easily preventable rookie error. This should already be executed automatically in multiple stages of their coding, merging and deployment pipelines with varying degrees of redundancy and thoroughness the same way it is for any tech company with more than maybe 10 developers. There is just no reason they shouldn't have prevented huge chunks of the now visible code issues, if were they triggering their own trash bots against their codebase with even the simplest prompt of "evaluate against good system design and architecture principles". This implies that they either weren't doing it at all, or maybe worse, ignored all the red flags it is capable of identifying after ingesting all of the system architecture guides and textbooks ever published online.

Anthropic is constrained in that some of the fixes which should be pushed to users are things which would have significant trade-off in the form of cost or context window, neither of which are palatable to them for reasons this community has discussed at length. But that constraint doesn't prevent them from running checks or applying fixes to their own code, which reveals the root cause: The problems Anthropic are facing are clearly cultural. They're pushing as much new shit as they can as quickly as possible and almost never going back to fix any of it. That's a choice.

I saw a couple of signs that there are at least a few people there who are capable, and who are trying to steer an out of control titanic away from the iceberg, but the codebase stinks of missing architectural plans which are being retrofitted piecemeal long after they were needed. That aligns with Anthropic's origin story, where OpenAI researchers accurately gauged how gullible venture capitalists are, but overestimated how much smarter they are than the rest of the world, and underestimated the value of practical experience building and running complex systems.

With the resources they have, even for a codebase of this unreasonable size, they could and should vibe code a much better version within a couple of months. That is not resounding praise for Claude, only a commentary on the quality of the existing code. Perhaps as a first step they could use their own "plan mode" which just appends a string that says not to make any edits, only to investigate and assess requirements...

Were I happy to watch the world burn, I'd start my own damn AI company that would do a much better job at this, because holy shit, people actually financed this trash.

Tl;dr, you're right that it doesn't bode well for their prospects of improvement, but it's not because there aren't many things they could be doing practically. It's because they refuse to point the gun somewhere other than their own feet.

[–] YourNetworkIsHaunted@awful.systems 3 points 16 hours ago (1 children)

Anthropic is constrained in that some of the fixes which should be pushed to users are things which would have significant trade-off in the form of cost or context window, neither of which are palatable to them for reasons this community has discussed at length.

I think I'm missing something somewhere. One of the most alarming patterns that Jonny found imo was the level of waste involved across unnecessary calls to the source model, unnecessary token churn through the context window from bad architecture, and generally a sense that when creating this neither they nor their pattern extruder had made any effort to optimize it in terms of token use. In other words, changing the design to push some of those calls onto the user would save tokens and thus reduce the user's cost per prompt, presumably by a fair margin on some of the worst cases.

[–] fiat_lux@lemmy.world 4 points 14 hours ago* (last edited 13 hours ago)

You're right, but Johnny rightly also identified the issue where Claude creates complex trash code to work around user-provided constraints while not actually changing approach at all (see the part about tool denial workarounds).

I think Anthropic optimized for appended system prompt character count, and measured it in isolation - at least in the project's beginning stages, if it's not still in the code. I assume the inefficiencies have come from the agent working with and around that requirement, backfiring horribly in the spaghetti you see now. Not only is the resulting trash control flow less likely to be caught as a problem by agents, especially compared to checking a character count occasionally, but it's more likely the agent will treat the trash code as an accepted pattern it should replicate.

Claude will also not trace a control flow to any kind of depth unless asked, and if you ask, and it encounters more than one or two levels of recursion or abstraction, it will choke. Probably because it's so inefficient, but then they're getting the inefficient tool to add more to itself and... there's no way to recover from that loop without human refactoring. I assume that's a taboo at Anthropic too.

A type of fix I was imagining would be something like an extra call like "after editing, evaluate changes against this large collection of terrible choices that should not occur, for example, the agent's current internal code". That would obviously increase the short term token consumption, context window overhead, and make an Anthropic project manager break out in a cold sweat. But it would reduce the gradient of the project death spiral by providing more robust code for future agents to copy paste that can be more cheaply evaluated, and require fewer user prompts overall to rectify obvious bad code.

They would never go for that type of long game, because they'd have to do some combination of:

  1. listening to all the users complain that they ran out of tokens too soon while creating the millionth token dashboard project, or,
  2. increase the limits for users at company cost, or,
  3. increase prices, or,
  4. sacrifice feature development velocity by getting humans to fix the mess / implement no-or-low-agent client-side tooling for common checks.

They should just set it all on fire, the abomination can't salvage the abomination.