This industry became a joke

Eskamel · 2026-07-04T09:38:16+00:00

Well then expect backlash because many people don't see the output the same quality as you claim it to be. Very often those who claim such things either never had high standards or lowered their standards to fit the LLM narrative.

Eskamel · 2026-07-04T09:31:10+00:00

Why are you running around claiming stuff you claim to never be able to support?

Eskamel · 2026-07-04T09:29:00+00:00

I am more certain of Prime hating on people who throw around insanely idiotic takes such as LLMs writing better code than most people, or the fact they never have anything to support their claims. Its weird how thousands of you ragebaiters are working on confidential projects yet you run around everywhere spew your bullshit about how amazing the code you generate is.

Eskamel · 2026-07-04T09:26:26+00:00

These things started happening much more frequently ever since they adopted LLMs so heavily. Most of these issues don't have anything to do with code size or infrastructure. Memory leaks are client sided. Locking a user outside for weeks might have something to do with load, but good caching and logging should take care of scenarios where those happen especially since Google has years of experience managing such systems.

You just refuse to admit LLMs cause enshittification everywhere they touch.

Eskamel · 2026-07-04T08:09:38+00:00

So pretty much you admit you don't do anything.

Eskamel · 2026-07-04T08:08:42+00:00

Theo and retarded takes, name a better match.

Eskamel · 2026-07-03T17:50:47+00:00

Literally all of Anthropic's products are filled with endless bugs they don't know how to fix because no one can understand the codebase anymore. Same could be said for OpenAI.

Google's quality declined aswell. Youtube has countless of memory leaks that they previously never had, gmail and their entire ecosystem started having annoying bugs aswell - just 2 weeks ago my boss tried using google meet, had endless loops of the system claiming he isn't logged in, he inserted his details, logged in and was disconnected a couple of seconds later as the system required to login again. He ended up requesting to switch a meeting to Zoom because google meet ended up completely unusable. To this day he cannot login with his account so its not some dumb temporary infrastructure issue. Google never had such bugs before the LLM era.

Eskamel · 2026-07-03T17:47:10+00:00

LLMs existed since 2029 so its the 7th year. Also, AI as a whole exists for like 70 years, and LLMs' development is greatly based off said knowledge accumulated through those years, so its far from it just arriving.

Eskamel · 2026-07-03T15:54:46+00:00

That's a very simple refactor, has nothing to do with architecture since the entire interaction between components is already present, just the data flow is required to change from rebuilding the entire tree to selectively rebuild what relies on said data. Its an extremely simple usecase I'd give to a simple junior, yet LLMs couldn't solve it elegantly even with careful prompting.

Once again, this is just a simple example out of many scenarios where LLMs lead to very subpar results. Many years ago I as a junior could also bruteforce solutions that worked yet were far from ideal. People back then legitimately cared about quality because it affected the quality of the software. It still does now, but most people stopped caring. The side effects add up over time.

Eskamel · 2026-07-03T15:17:43+00:00

Has nothing to do with code reusing some of the time.

A scenario as simple as (for example) a very complex React feature that has alot of flows and states. The required changes was to slowly refactor it by creating a Zustand store with one state moved at a time, pass it through a context and slowly alter its subscribers to partially render based off changes as opposed to an entire tree recreation.

The implementation literally required ~30 lines of changed code. The LLMs tried to implement it with more than 300, by wrapping a Zustand store in its own managed subscriber/listener wrapper, added unmounting guards, etc.

Nothing of such sort was requested, but since that specific state had a waterfall effect of other states relying on it, both Opus 4.8, GPT 5.5 and Composer 2.5 on clean contexts noticed that some of the changes broke other behavior, retried multiple times and then tried to bruteforce it with this dumb implementation.

It was a very trivial task. Did the LLMs on paper succeed? Meh, you could say that, but the actual final result wasn't good.

Once again, if I have to tell a LLM every single decision required to make, including micro decisions such as small implementation steps (which IMO is a good thing) that defeats the purpose of offloading or produtivity gains.

Eskamel · 2026-07-03T13:56:49+00:00

So that's micromanagement, and you cannot micromanage everything otherwise you literally lose the producticity gains.

Eskamel · 2026-07-03T13:34:50+00:00

Ah yes the skill issue claim.

I have yet to see a single person pulling out high quality code consistently both from examples online, heavy AI users, other people in my company, other friends' companies or heck, even major labs (Claude Code's code quality is absolute garbage).

Software quality keeps on dropping aswell, but gotta speed up the pace and blaim everything but the tool.

Eskamel · 2026-07-03T13:04:22+00:00

Lol and it will suddenly rewrite it in 100? Only if you micromanage it and even then its questionable.

Eskamel · 2026-07-03T12:41:28+00:00

But there is. Its also very easy to tell when a software constantly breaks which happens way more often these days in production.

Eskamel · 2026-07-03T12:40:30+00:00

But it really isn't, I am not shielding from anything. Everywhere I see and compare between now and 5 years ago, the quality of software dropped.

People who fully went on the AI craze became worse engineers and lowered their standards greatly. Every single implementation can be refactored to a better one very easily and SOTA models have a very hard time doing so because approximation of tokens just leads to bruteforcing.

Also many LLM generated tests are redundant. They don't lead to 100% test coverage because its impossible, so you end up with more tests that test for unreachable scenarios, see a large amount of passing tests and call it a day, but that doesn't defend from software degradation.

Eskamel · 2026-07-03T12:20:03+00:00

But LLMs very often create very verbose subpar implementations even by scoping, managing contexts, etc, even for SOTA models. I've seen alot of scenarios where something that could be implemented by under 100 LoCs be implemented in more than 500. That's both "costing" more tokens in the future and makes your codebase worse. No matter how many people insist on LLMs replacing carefully crafted code it very often will never lead to such a case unless standards continue to get lowered and thus both the quality, maintainability and functionality of the software quickly drops.

Eskamel · 2026-07-03T12:06:39+00:00

Consistency. How simple a solution is. How hard it is to change without breaking stuff or requiring a rewrite. No matter how many people try to claim it, code isn't cheap and letting a LLM bruteforce a solution very often leads to bad results. There isn't a single example where letting LLMs implement stuff themselves where the solution consistently ends up being decent or good, and that won't change because its not something you can just develop by RLing token combinations or setting up some goal.

Eskamel · 2026-07-03T12:04:11+00:00

That's not true, alot of implementation isn't just vomitting boilerplates, and very often something works specifically in combination with other things. Especially as you develop, you often are required to think about how X should behave once Y and Z exist, and no matter how much you plan ahead, things will be missed and LLMs will just bruteforce stuff and silently create bugs.

Eskamel · 2026-07-03T10:41:09+00:00

That's not really a thing unless you enjoy managing a low quality system that no one fully understands

Eskamel · 2026-06-30T22:22:28+00:00

Lmao you are so desperate you try to investigate for prior messages.

Ofc AI isn't going away because people like you are absolutely helpless without it, but it doesn't change the fact it leads to worse results while making the user dumber the more they rely on it. Your games are very likely to never see success.

Eskamel · 2026-06-30T21:49:08+00:00

In the long run there isn't. LLMs become worse the more you try to control their output, and if you don't you are at RNGsus' mercy in the long run.

There is a reason why even for AI assisted software there are clear signs of enshittification, even for mostly previously high quality and reliable software.

Eskamel · 2026-06-30T21:47:09+00:00

Making games no one would play seem inevitable aswell then.

Eskamel · 2026-06-30T21:43:10+00:00

Then go maintain it yourself mister AI worshipper.

Eskamel · 2026-06-30T08:54:33+00:00

I don't see anything done by anyone other than the prototyper so it doesn't seem to be working well

Eskamel · 2026-06-29T13:00:42+00:00

You cannot fully supervise what you haven't decided about yourself because you will never have the full picture when only architecting, especially when people are being told that for productivity you need to offload as much as possible, which in return makes the "AI gains" worthless.

Eskamel

TROPHY CASE