LLMs will not replace proper software developers

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How much code does an LLM create for you?

  • 0% I don't allow it

    Votos: 19 24.1%
  • 0-5% very low

    Votos: 11 13.9%
  • 5-10%

    Votos: 6 7.6%
  • 10-20%

    Votos: 6 7.6%
  • 20-30%

    Votos: 5 6.3%
  • 30-40%

    Votos: 3 3.8%
  • 40-50%

    Votos: 0 0.0%
  • 50-60%

    Votos: 0 0.0%
  • 70-90%

    Votos: 4 5.1%
  • 90-100%

    Votos: 7 8.9%
  • I am not a programmer.

    Votos: 18 22.8%

  • Total de votantes
    79

ArgonianVoter

kiwifarms.net
Registrado
24 de Feb, 2025
I am so tired of hearing it, if you're a coder I know you're tired of it too.

so let's take a poll to shut them up.
And Remember, LLMs need training data in order to produce output.
 
Anyone work for an employer that is trying to force it? I don't mean have it present as an assistant, or a tool to generate boilerplate code, documentation, and unit tests. I mean make you first write everything with it (new feature code, bug fixes, etc) , then review the output after. They have metrics that track your use of it to ensure you are accepting its code output.

My job says they're going to start that within the year, and I'm considering finding a different job. I know you can game the metrics, but still, this is retarded and will remove the last part of my job that I enjoy.
 
Code autocomplete is fantastic and improves my flow by a lot. LLM code is hot garbage that I have to check very carefully, so I might as well do it from scratch.

I don't code in languages that are popular for LLMs, so maybe you guys have a different experience. But I can say with certainly that current "AI" products suck balls for VHDL, verilog, and embedded development in C and assembly. Especially Risc V or ARM. Literally don't even get the basics right.
 
Anyone work for an employer that is trying to force it? I don't mean have it present as an assistant, or a tool to generate boilerplate code, documentation, and unit tests. I mean make you first write everything with it (new feature code, bug fixes, etc) , then review the output after. They have metrics that track your use of it to ensure you are accepting its code output.

My job says they're going to start that within the year, and I'm considering finding a different job. I know you can game the metrics, but still, this is retarded and will remove the last part of my job that I enjoy.
i'm so sorry dude. are you the one who voted for 90% xD
 
Text is the universal interface. Any profession which largely involves the generation of text is going to be made more competitive by the introduction of LLM. Boilerplate code monkey tasks are undoubtedly going to be replaced by automation. LLMs haven't even been around that long in the grand scheme of things, so even if improvement tapers off, I imagine we're going to continue to see more and more adoption as time goes on. Will it put you out of a job right away? Probably not. But if you think software development is going to stay the same forever, you're sorely mistaken.

Everyone was hella smug, sneering "learn to code" at journalists that were being rendered irrelevant by basic text generation. The endless march of modernity and innovation tramples us all. Extrapolate this out 20, 30, 50 years? Better swing that hammer faster, John Henry, or the locomotive will run you over.
 
Here's my take on this:

Artificial intelligence is advancing at a pace that suggests software developers, as a profession, may eventually be replaced or dramatically diminished. What once required years of education and experience—writing functional code, debugging systems, optimizing performance—can now be done in seconds by AI systems trained on vast repositories of software knowledge. As these systems improve, the economic and practical incentives to replace human developers become increasingly compelling.

At its core, software development is a process of translating human intent into machine-readable instructions. This translation is precisely what large language models and code-generating AI systems excel at. Already, AI can generate entire applications from plain-language prompts, refactor legacy code, detect vulnerabilities, and write test suites automatically. As models gain better reasoning abilities and deeper contextual awareness, the gap between “assistance” and “autonomy” will continue to close.

From a business perspective, AI replacement is inevitable. Human developers are expensive, require ongoing training, take breaks, and are prone to burnout and inconsistency. AI systems, by contrast, can work continuously, scale instantly, and produce standardized output. For companies under pressure to reduce costs and accelerate development cycles, replacing large development teams with a small number of engineers overseeing AI systems becomes an attractive proposition.

Moreover, much of modern software development is repetitive and formulaic. CRUD applications, API integrations, frontend interfaces, and cloud infrastructure configurations follow well-established patterns. These patterns are ideal for automation. As AI systems internalize best practices and architectural standards, human involvement becomes less necessary. Over time, what remains for developers to do may shrink to such a degree that the profession no longer resembles its current form.

Historical precedent supports this trajectory. Many technical roles—from typists to assembly-line workers—were once considered indispensable until automation rendered them obsolete or marginal. Software development, despite its intellectual veneer, is still a form of production work. Once machines can reliably produce software that meets functional and business requirements, the justification for human developers weakens.

Finally, as AI systems begin to design other AI systems, the replacement loop accelerates. Tools that can self-improve, debug their own code, and adapt to new frameworks without human retraining threaten to eliminate the final dependency on human expertise. In such a future, software development becomes an automated process managed by AI, leaving human developers largely displaced.

I hope this insight added something to the conversation! Ask me if you'd like more.
 
I had a team of 20 pajeets working under me. Now I have claude. Guess which one works better?

My code is 95% agent generated nowadays with very little human intervention. Cursor will automatically include all the code in a project in the context window and look up all the API docs on the internet - people aren't just copy pasting code into the chatgpt window, the tools have been advancing at an astonishing rate.

Humans are for checking if the output is good.
 
Artificial intelligence is advancing at a pace that suggests software developers, as a profession, may eventually be replaced or dramatically diminished. What once required years of education and experience—writing functional code, debugging systems, optimizing performance—can now be done in seconds by AI systems trained on vast repositories of software knowledge. As these systems improve, the economic and practical incentives to replace human developers become increasingly compelling.

At its core, software development is a process of translating human intent into machine-readable instructions. This translation is precisely what large language models and code-generating AI systems excel at. Already, AI can generate entire applications from plain-language prompts, refactor legacy code, detect vulnerabilities, and write test suites automatically. As models gain better reasoning abilities and deeper contextual awareness, the gap between “assistance” and “autonomy” will continue to close.

In order to holistically operationalize scalable synergies across cross-functional stakeholder ecosystems, we must strategically leverage AI-enabled paradigm shifts that proactively unlock value-adjacent optimization vectors while simultaneously aligning future-forward innovation roadmaps with data-driven insights, continuous feedback loops, and outcome-oriented deliverables. This initiative will empower enterprise-grade transformation by dynamically orchestrating best-in-class solutions, fostering actionable intelligence, and catalyzing sustainable growth through iterative alignment, adaptive governance frameworks, and KPI-centric value realization, all while maintaining an unwavering commitment to excellence, agility, and next-generation thought leadership.
 
In order to holistically operationalize scalable synergies across cross-functional stakeholder ecosystems, we must strategically leverage AI-enabled paradigm shifts that proactively unlock value-adjacent optimization vectors while simultaneously aligning future-forward innovation roadmaps with data-driven insights, continuous feedback loops, and outcome-oriented deliverables. This initiative will empower enterprise-grade transformation by dynamically orchestrating best-in-class solutions, fostering actionable intelligence, and catalyzing sustainable growth through iterative alignment, adaptive governance frameworks, and KPI-centric value realization, all while maintaining an unwavering commitment to excellence, agility, and next-generation thought leadership.
kamala, that you?
 
No, but LLMs will probably replace Pajeets because it can code better than they can, which is good.
Unless the h1b is ended they're gonna hire a single pajeet to write prompts and debug the errors with more prompts to replace coding teams because it makes line go up for long enough to swindle investors
 
I'm starting to use ShatGPT to write small functions or userscripts that I'm too lazy to do myself.


When it's short/simple, it doesn't require much testing and is more likely to get it right on the first try. For that Bluesky one I autistically described the level of element in the DOM to remove.
 
What's the name of the game to get employed nowadays? Persuading someone to hire you. What is more immediately persuasive to an ignorant person in a hiring position? A robotic slave who can produce convincing yet mediocre work, or a living person with all the headaches that implies?

This is the only reason LLMs will replace workers. Then when that mess has to be cleaned up they will hire people who promise the moon and how they will surely fix the AI code and monitor it saar. By that point you will probably live in a major competency crisis with nobody around who can actually fix it though.
 
The big problem with software is that too much code is being written with too little thought put into it. LLMs not only don’t help anything, they make that particular problem a hell of a lot worse.
Agreed
I do use Claude for some boilerplate, but I've found anything more complicated than that inevitability ends up riddled with errors and shit anti-patterns. Lots of copypasta, too. The amount of time I take cleaning it up tends to be at least as long as it takes to design and implement from scratch myself.

It can be good for rapid prototypes, but I have to rewrite from scratch once the idea is proofed.

kamala, that you?
Too many big words.
 
Watch and laugh as Microsoft wagies are forced to use AI and it keeps fucking up


Lol, that Stephen Toub guy is pretty big in the dotnet sphere, I'd say he's getting Copilot rammed down his fucking throat by Microsoft.
He just needs to call Copilot a stalker child and threaten it with eternal prison.

Regarding LLMs, in my experience so far:
1. They work great for simple tasks that have a lot of high-quality examples, such as college assignments and initial boilerplates.
2. They're dog shit when there's few examples or on anything that lacks conceptual integrity, such as big closed-source code bases that uses a bunch of internal conventions and terminology.

I think the AI thing will run out of steam in the next couple years, maybe even in 2026, then the field will go quiet for the next decade or so. I think the messaging about it being the "age of AI" rather than the "age of LLMs" makes it difficult to clearly reconcile the abilities and limitations of LLMs with the level of hype.
 
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