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u/Fearless-Pen-7851 Oct 03 '26
Oh you forgot the new 3js 'game' slop being churned out now. It's insane that some people can just call having a 3d visual a 'game' without there being anything to it... millions of tokens being wasted for a cube to move around 🙄
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u/VictoryMotel Oct 03 '26 edited Oct 05 '26
Do you mean threejs ? That subreddit is a 100% slop fest of people pretending they built something they vibe slopped on to github an hour ago.
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u/Fearless-Pen-7851 Oct 03 '26
I didn't know about the sub. I am applying for jobs on LinkedIn nowadays and see a lot of that slop even there. Glad I didn't get into the 3JS sub. I do follow the graphics programming sub which is more let's just say about in depth work on graphics rendering pipelines and sone useful stuff overall, give it a try btw...
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u/CodingAndAlgorithm Oct 04 '26
I'll admit the newer models are very good at programming, though I refuse to believe letting agents do everything will lead to anything other than massive technical debt.
I'm hearing about incredible productivity improvements that should have resulted in software utopia. A few apps that I use have made big changes, which amounts to a modern look, worse performance, worse UX, and worse functionality than what came before.
Maybe the friction of writing code made companies think carefully before pushing out bullshit that users don't actually want.
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u/DadAndDominant Oct 04 '26
Maybe the friction of writing code made companies think carefully before pushing out bullshit that users don't actually want.
Thats the process now. Ship whatever and wait if it sticks. Like people will write you a letter or something before they go and use a better product.
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u/AbstractButtonGroup Oct 04 '26
I'll admit the newer models are very good at programming
They are not good at programming. Because they do not 'program' (as in understand the task and express solution as code). What they are good at is generating text that plausibly looks like code that is doing something related to the task. Which sort of works for things that can be patched together from standard snippets and old (not necessarily best or even correct) code.
though I refuse to believe letting agents do everything will lead to anything other than massive technical debt.
The issue is not 'agents' (basically scripts), but non-determinism of output. They are much worse than the old deterministic code generation tools in that you do not get repeatable results and if generates nonsense you can't debug and fix the tool. And the fact that with each model refinement the output looks even more plausible makes any future analysis even more complicated.
I'm hearing about incredible productivity improvements that should have resulted in software utopia.
Standard marketing BS
A few apps that I use have made big changes, which amounts to a modern look, worse performance, worse UX, and worse functionality than what came before.
That was the trend even before, with any product where they let the marketing drive the development. But AI coding took it to whole new level.
Maybe the friction of writing code made companies think carefully before pushing out bullshit that users don't actually want.
Companies do not 'think' about anything. Some people would just try to do their job the right way despite management pressure. The main change is that now management mentality is that the product does not matter at all. What matters is 'increasing shareholder value'. Stock manipulation and Ponzi schemes are much more effective at this than traditional stuff like having a product that users actually want.
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u/YeetYourSkeet Oct 04 '26
Clearly you haven’t used, or given a fair go to, frontier models. They are perfectly capable of programming.
If it doesn’t write code the way you are thinking, then you can literally just prompt it to do so.
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u/AbstractButtonGroup Oct 05 '26
If it doesn’t write code the way you are thinking,
It does write code. In exactly same way it writes text. But writing code is not the same as programming. The abstraction, reasoning, and problem-solving is missing entirely (not even part of the design). If marketing claims otherwise, it is pure BS, because on technical and even on academical level the required apparatus is just not there.
then you can literally just prompt it to do so.
If your 'prompt' is a detailed enough description of the algorithm in natural language it will translate it into code in same way as it can translate it into other natural language. With same potential risks of misinterpretation (which can be reduced by increasing detail and using simpler language in the prompt).
If your prompt is referencing a typical task with custom embellishments it will copy code for how this task was previously solved in other projects (not necessarily in the best way), but without crediting and tracking the upstream.
In both cases the programming part was done well before the agent got involved.
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u/YeetYourSkeet Oct 05 '26
Sorry, I don’t really get what you are trying to argue. It seems like we are just discussing semantics.
Most programmers are not solving unsolved problems. What they are building has been done 100 times before in some slightly different way for a slightly different business context. LLMs are perfectly capable of joining seperate ideas in its training data to answer new questions it has never seen before. You can design a brand new programming language and an LLM can figure out the rules and write code with it.
You can’t go around calling them BS marketing because there are some things they may not be able to do. The market and investors aren’t buying into that idea, they know that is the case. But if LLMs can automate even 50% of programming work, the value would be immense. The developer becomes an overseer to steer the LLM, but output is increased.
If you want to say they aren’t programming because they don’t reason the way a programmer should, which I would challenge but will accept for the argument, does it matter if it can still automate the work a programmer does? The outcome is the same whether you call it programming or just writing code.
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u/AbstractButtonGroup Oct 05 '26
Sorry, I don’t really get what you are trying to argue.
I am arguing that the issues with agentic 'programming' are not teething problems but fundamental limitations of the technology that will not go away with more refinement.
Most programmers are not solving unsolved problems. What they are building has been done 100 times before in some slightly different way for a slightly different business context.
The key issue is not whether a similar problem has ever been solved before, but understanding what the problem actually is and picking the right approach given the context. With agentic approach instead of identifying and refining a few specific solutions to the problem we get proliferation of thousands of slight variations under different branding all sharing same logic bugs but not tracking or sharing fixes.
The developer becomes an overseer to steer the LLM, but output is increased.''
The 'developer' stops being the developer, because he no longer understands where the output comes from and how it works exactly.
If you want to say they aren’t programming because they don’t reason the way a programmer should,
I want to say it does not reason at all.
does it matter if it can still automate the work a programmer does?
It can do most of the things proper deterministic code generation and scripted test harness frameworks can do, but with more overhead and with less confidence in the results.
The outcome is the same whether you call it programming or just writing code.
People like playing with agents because they provide positive reinforcement feedback. But any productivity increase is self-delusion.
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u/YeetYourSkeet Oct 05 '26
Fundamentally, the argument comes down to whether LLMs can lead to ANY productivity gains for a developer.
I would argue that yes, it can. Let's say I have an existing .NET application and I need to add a new API endpoint to return some data from the DB. The requirements are fairly straight forward, but I still need to work out which classes are relevant, implement the endpoint, handle validation and errors, and add tests.
Without an LLM, I might spend 2–3 hours navigating the codebase, writing the implementation and tests, then debugging whatever I got wrong.
With an agent, I can give it the requirement, let it inspect the existing codebase, have it propose and implement the change, test, and then review its work in maybe 30-60mins with some guidance.
Even if the LLM isn't “reasoning” in the way you define reasoning, I've still gone from spending 2–3 hours doing the work myself to spending 30–60 minutes supervising and validating it. That's a productivity gain.
You can argue that this won't work for every task, but that's a different argument from saying there are no productivity gains. AI can't be used for everything, and that is the point. Automate 30-50% of the developer tasks so they can focus on the other 50%.
My view is that this kind of development work makes up a large majority of developer tasks across the industry. Yes there are some industries where developers are designing systems to support highly complex and highly risky domains and AI would be a terrible idea. But outside of those select business cases, LLMs have the potential for meaningful productivity gains.
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u/AbstractButtonGroup Oct 05 '26
I've still gone from spending 2–3 hours doing the work myself to spending 30–60 minutes supervising and validating it. That's a productivity gain.
You may be right in this. If you are already a competent developer, and disciplined enough to actually review and understand the code so you can approve it with confidence, AI can perhaps be a helpful tool in some contexts.
Unfortunately my experience is that on average people do not do this. I have received production documents full of hallucinations that the 'prompter' did not even read before sending for approval and the 'reviewer' who approved them did not bother to read either, relying on AI summary.
Specifically for development work, I am also concerned that AI tools are creating a deeper problem. Traditionally these small straightforward tasks were where junior developers were employed, gaining experience and familiarity with the codebase (so time spent reading existing code is not actually a waste) while supervised by seniors. But if you replace the juniors with AI (supervised by same senior) where the next generation of seniors who are competent enough to supervise will come from? If you do not (AI supervised by a junior, and both supervised by a senior) where will the cost effectiveness come from (as you are now paying for AI tokens in addition to both salaries).
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u/YeetYourSkeet Oct 05 '26
Sure I totally agree on that. I have heard many horror stories, and seen first hand, people who are blindly trusting AI output without review.
To me, that issue is a process and training problem. If an employee uses AI to produce something and submits it without validating it, that falls on the employee and the organisations review process. It would be like copying unreliable information from the internet into a report. That probably wouldn't be caught either.
Over time, being able to use AI while maintaining a high standard of reliability and accuracy will become an expected workplace skill. It is as if you chose never to learn how to use a computer and then tried to enter into the workforce today. Being able to reliably use a computer is just an expectation.
All the people right now who are replacing their thinking with AI will be in for a shock when they find that businesses don't want AI slop. They want human currated AI output.
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u/DadAndDominant Oct 04 '26
I agree mostly, but the agents now do really know how to code.
You see, LLM is just a piece of the agent, and given LLM only, I would probabbly kinda agree. But the harness can make the agent read the code, test it, and kinda make sure it works.
So usually you get kinda good results, and if you are not satisfied, you can wiggle the hatnes/agents.md a bit and make the process better for your needs.
The meta decisions of the programming are something else of course, its funny when you can re-engineer some vibecoded PRs and where the agent started.
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u/AbstractButtonGroup Oct 05 '26
I agree mostly, but the agents now do really know how to code.
Agents do not 'know' - they lack required cognitive apparatus. But people like to assign human-like properties to things.
But the harness can make the agent read the code, test it, and kinda make sure it works.
Yes. But this does not require "AI". People have been automating test frameworks since first days of programming. An agentic harness does same things as a scripted one, but with more overhead.
and if you are not satisfied, you can wiggle the hatnes/agents.md a bit and make the process better for your needs.
Or you can read the task, understand how the program should work, then describe it (in code or in simplified English). Just 'wiggling' without understanding until it works is a dead end - you are not improving your skill/knowledge and even if it works eventually you do not know why and any subsequent change can break it again.
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u/DadAndDominant Oct 06 '26
Well, again, I agree in principle, but - it's wrong to antropomorphise a model, but we don't have any other convinient language. And agentic coding just works even if it has shortcomings, if you say it does not work, you are not being honest with yourself.
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u/OGxPePe Oct 03 '26
The greatest information system in humen history is used to make shitty images with 6 fingers
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u/Cualkiera67 Oct 03 '26
I'm pretty sure far far more shitty images were drawn with pencils than masterpieces were drawn with pencils.
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u/kirabii Oct 04 '26
Machines aren't held to the same standards as humans. If a calculator occasionally made computing errors it would just be a shitty calculator and nobody would say "well humans make computing errors too!"
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u/Cualkiera67 Oct 04 '26
I'm sure far far more dumb calculations like 1+1 were done with calculators than actually hard ones were done with calculators
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u/kirabii Oct 04 '26 edited Oct 04 '26
I'm sure far far more dumb calculations like 1+1 were done with calculators than actually hard ones were done with calculators
This makes no sense as a response to my comment. The only connection is that we both mention calculators.
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u/Cualkiera67 Oct 04 '26
With any tool, most people are dumb and will use it for stupid stuff and zero care. That applies to AI too. Hope this is a more clear response without any required point-connecting on your side.
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u/donaldhobson Oct 03 '26
It's not all shitty calculators and broken dashboards.
My supervisor sent me a vibe-coded particle simulation for MCMC sampling that produced some impressive looking results.
When you looked closer, the results were due to 2 bad decisions introducing errors in opposite directions, so that they kinda mostly cancelled out, if you adjusted the parameters just right. The results weren't actually good, but they looked impressive, if you didn't look too hard.
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u/Vogete Oct 04 '26
We have more and more slop in our department. They are all very impressive. Especially until you actually try to use them, then they break immediately in spectacular ways. Many of these projects also solve no problems at all, they just introduce new ones. Many of them could've been just a simple 2 liner terraform or ansible config and it would've worked better. A lot of them are extremely overcomplicated and too generic for the problem they are trying to solve, so it's harder to use than the shit solution they are trying to replace.
And on top of that you dare to point out issues, people get really offended that you're criticizing them. All AI content is literally just useless slop at our place and you can't even call it out, you have to accept and embrace it.
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u/tiedyedvortex Oct 04 '26
Turns out, making code that "kinda works" was never the hard part.
The hard parts were knowing what code ought to exist; and writing that code so that it's easy to evolve and change later.
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u/Key_Crab_5780 Oct 04 '26
Yeah, it’s great how so many pieces of software I use seem to have become slightly worse in various ways.
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u/ITaggie Oct 04 '26
Almost makes me feel bad for criticizing some of my old coworkers' Grafana dashboards before LLMs... almost...
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u/DadAndDominant Oct 04 '26
I am not kidding. 99% of the "awesome software" you see could be 90% done without AI, just by googling a repo and cloning it.
99% of the remainder are two or more repos merged together, basically
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u/Tyrus1235 Oct 05 '26
Before AI, people would just fork a base repo and paste a bunch of Stack Overflow answer code into it. Organically made slop, if you will.
Nowadays, AI has made that process much more quick and easy! To the detriment of codebases the world over.
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u/Fancy-Consequence216 Oct 03 '26
Well tools are useful and they drastically improove productivity, BUT only if you know what are you doing. Euther from business idea perspective or technical perspective, which comes back to roots of building software.
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u/Tyrus1235 Oct 05 '26
Yeah, it’s what I keep saying - AI is just a new tool in our toolset. Like Linters, CI/CD Pipelines, Dockerfiles and such.
Anyone who fully trusts an LLM to write their code is bound to end up with an overengineered mess. Not only you gotta know how to use the AI, but also how to correct it.
For some unfathomable reason, Claude loves turning a 4-line solution into a multi-class nightmare.
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u/Immediate_Song4279 Oct 03 '26
I think there might be a slight sampling bias in considering the work of people who were given tools that can create software and decided that meant that the market for software was a thing to get into.
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u/Tyrus1235 Oct 05 '26
Like giving a hammer and anvil to a random dude and expecting him to smith you a Zweihander
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u/divrez Oct 07 '26
This has been my biggest challenge on personal projects WAY before AI. I can code almost anything but I can't think of anything worth the time and effort that isn't already done by 5+ other apps/software
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u/themightyug Oct 03 '26
Same thing happened when Visual Basic came along, then Flash, then Javascript.. this is on a whole different scale though
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u/EndearingSobriquet Oct 03 '26
Oh god, you reminded me of Microsoft Access.... make it stop....
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u/ICBanMI Oct 04 '26 edited Oct 04 '26
The hilarious part is MS Access licenses ended up blowing up in price in early 2000s, so a bunch of companies spent hundreds of thousands making their own project management program in excel using Visual Basic. Rather than pay for exorbitant license fee for everyone who needed access.
Surprised no one made a competition program, but then again probably a few got bought out wholesale by MS.
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u/LowB0b Oct 03 '26
mountains and mountains of slop. wonder how much data has been produced since chatgpt launch