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I don't care how well your "AI" works

fokus.cool

231–240 of 808 posts

Re: I don't care how well your "AI" works

#231

Everytime I read one of these "I don't use AI" posts, the content is either "my code is handcrafted in a mountain spring and blessed by the universe itself, so no AI can match it", or "everything different from what I do is technofascism or ". Maybe Im missing something, but tech is controlled by a handful of companies - always have been; and sometimes code is just code, and AI is just a tool. What am I missing?

? Maybe Im missing something, but tech is controlled by a handful of companies - always have been

I guess it depends on what you define as "tech", but the '80s, '90s, and early '00s had an explosion of tiny hardware and software startups. Some even threatened Intel with x86 clones.

It wasn't until the late '90s that NVIDIA was the clear GPU winner, for instance. It had serious competition from 3DFX, ATI, and a bunch of other smaller companies.

Re: I don't care how well your "AI" works

#232
post #110

Earlier quoted context omitted.

> What exactly is being de-valuated for a profession You're probably fine as a more senior dev...for now. But if I was a junior I'd be very worried about the longevity I can expect as a dev. It's already easier for many/most cases to assign work to a LLM vs handholding a human through it. Plus as an industry we've been exploiting our employer's lack of information to extract large salaries to produce largely poor qua…

> assign work to an LLM This is just not happening anywhere around me. I don't know why it keeps getting repeated in every one of these discussions. Every software engineer I know is using LLM tools, but every team around me is still hiring new developers. Zero firing is happening in any circle near me due to LLMs. LLMs can not do unsupervised work, period. They do not replace developers. They replace Stack Overflow…

Well your anecdote is clearly at odds with absolutely all of the macro economic data.

Re: I don't care how well your "AI" works

#233
post #215

Earlier quoted context omitted.

> The era of software mass production has begun. We've been in that era for at least two decades now. We just only now invented the steam engine. > I wonder how long it takes until this comes all crashing down. At least one such artifact of craft and beauty already literally crashed two airplanes. Bad engineering is possible with and without LLMs.

There's a buge difference between possible and likely. Maybe I'm pessimistic but I at least feel like there's a world of difference between a practice that encourages bugs and one that allows them through when there is negligence. The accountability problem needs to be addressed before we say it's like self driving cars outperforming humans. On a errors per line basis, I don't think LLMs are on par with humans yet

Knowing your system components’ various error rates and compensating for them has always been the job. This includes both the software itself and the engineers working on it.

The only difference is that there is now a new high-throughput, high-error (at least for now) component editing the software.

Re: I don't care how well your "AI" works

#234
post #200

I get that some people want to be intellectually "pure". Artisans crafting high-quality software, made with love, and all that stuff. But one emerging reality for everyone should be that businesses are swallowing the AI-hype raw. You really need a competent and understanding boss to not be labeled a luddite, because let's be real - LLMs have made everyone more "productive" on paper. Non-coders are churning out small…

> You really need a competent and understanding boss to not be labeled a luddite, because let's be real - LLMs have made everyone more "productive" on paper. I am actually less productive when using LLMs because now I have to read another entities code and be able to judge wether this fits my current business problem or not. If it doesn't, yay refactoring prompts instead of tackling the actual problem. Also I can wri…

> I am actually less productive when using LLMs because now I have to read another entities code and be able to judge wether this fits my current business problem or not.

You don’t have to let the LLM write code for you. They’re very useful as a smart search engine for your code base, a smart refactoring tool, a suggestion generator, and many other ways.

I rarely have LLMs write code for me from scratch that I have to review, but I do give them specific instructions to do what I want to the codebase. They can do it much faster than I can search around the codebase and type out myself.

There are so many ways to make LLMs useful without having them do all the work while you sit back and judge. I think some people are determined to get no value out of the LLM because they feel compelled to be anti-hype, so they’re missing out on all the different little ways they can be used to help. Even just using it as a smarter search engine (in the modes where they can search and find the right sections of right articles or even GitHub issues for you) has been very helpful. But you have to actually learn how to use them.

> If my job forced me to use these tools, congrats, I'll update my address to some hut in a forrest eating cold canned ravioli for the rest of my life because I for sure dont wanna work in a world where I am forced to use dystopian big tech machines I cant look into.

Okay, good luck with your hut in the forest. The rest of us will move on using these tools how we see fit, which for many of us doesn’t actually include this idea where the LLM is the author of the code and you just ask nicely and reject edits until it produces the exact code you want. The tools are useful in many ways and you don’t have to stop writing your own code. In fact, anyone who believes they can have the LLM do all the coding is in for a bad surprise when they realize that specific hype is a lie.

Re: I don't care how well your "AI" works

#235
post #183

I always thought years of experience in a language was a silly job requirement. LLMs allow me to write Rust code as a total Rust beginner and allows me to create a valuable SaaS while most experienced Rust developer never built anything that made $1 outside of their work. I wouldn't say devaluation, my programming experience definitely helps with debugging. LLMs eliminate boilerplate, not engineering judgement and pr…

I think when the author says

> “We programmers are currently living through the devaluation of our craft”

my interpretation of what the author means by devaluation is the general trend that we’re seeing in LLMs

The theory that I hear from investors is as LLMs generally improve, there will exist a day where a LLMs default code output, coupled with continued hardware speeds, will become _good enough_ for the majority of companies - even if the code looks like crap and is 100x slower than it needs to be

This doesn’t mean there won’t be a few companies that still need SWEs to drop down and do engineering, but tbh, the majority of companies today just need a basic web app - and we’ve commoditized web app dev tools to oblivion. I’d even go as far to argue that what most programmers do today isn’t engineering, it’s gluing together an ecosystem of tooling and or API’s.

Real engineering seems to happen outside of work on open source projects, at the mav 7 on specialized teams, or at niche deeply technical startups

EDIT: I’m not saying this is good or bad, but I’m just making the observation that there is a trend towards devaluing this work in the economy for the majority of people, and I generally empathize with people who just want stability and to raise a family within reasonable means

Re: I don't care how well your "AI" works

#236
This post raises genuine concerns about the integration of large language models into creative and technical work, and the author writes with evident passion about what they perceive as a threat to human autonomy and craft. BUT… the piece suffers from internal contradictions, selective reasoning, and rhetorical moves that undermine its own arguments in ways worth examining carefully.

My opinion: This sort of low-evidence writing is all too common in tech circles. It makes me wish computer science and engineering majors were forced to spend at least one semester doing nothing but the arts.

The most striking inconsistency emerges in how the author frames the people who use LLM tools. Early in the piece, colleagues experimenting with AI coding assistants are described in the language of addiction and pathology: they are “sucked into the belly of the vibecoding grind,” experiencing “existential crisis,” engaged in “harmful coping.” The comparison to watching a friend develop a drinking problem is explicit and damning. This framing treats AI adoption as a personal failure, a weakness of character, a moral lapse. Yet only paragraphs later, the author pivots to acknowledging that people are “forced to use these systems” by bosses, UI patterns, peer pressure, and structural disadvantages in school and work. They even note their own privilege in being able to abstain. These two framings cannot coexist coherently. If using AI tools is coerced by material circumstances and power structures, then the addiction metaphor is not just inapt but cruel — it assigns individual blame for systemic conditions. The author wants to have it both ways: to morally condemn users while also absolving them as victims of circumstance.

This tension extends to the author’s treatment of their own social position. Having acknowledged that abstention from LLMs requires privilege, they nonetheless continue to describe AI adoption as a “brainworm” that has infected even “progressive hacker circles.” The disgust is palpable. But if avoiding these tools is a luxury, then expressing contempt for those who cannot afford that luxury is inconsistent at best and self-congratulatory at worst. The acknowledgment of privilege becomes a ritual disclaimer rather than something that actually modifies the moral judgments being rendered.

The author’s claims about intentionality represent another significant weakness. The assertion that AI systems being resource-intensive “is not a side effect — it’s the point” is presented as revelation, but it functions as an unfalsifiable claim. No evidence is offered that anyone designed these systems to be resource-hungry as a mechanism of control. The technical requirements of training large models, competitive market pressure to scale, and the emergent dynamics of venture capital investment all offer more parsimonious explanations that don’t require attributing coordinated malicious intent. Similarly, the claim that “AI systems exist to reinforce and strengthen existing structures of power and violence” is stated as though it were established fact rather than contested interpretation. This is the central claim of the piece, and yet it receives no argument — it is simply asserted and then built upon, which amounts to begging the question.

The essay also suffers from a pronounced selection bias in its examples. Every person described using AI tools is in crisis, suffering, or compromised. No one uses them mundanely, critically, or with benefit. This creates a distorted picture that serves rhetorical purposes but does not reflect the range of actual use cases. The author’s friends who share their anti-AI sentiment are mentioned approvingly, establishing clear in-group and out-group boundaries. This is identity formation masquerading as analysis — good people resist, compromised people succumb.

There is a false dichotomy running through the piece that deserves attention. The implied choice is between the author’s total abstention, not touching LLMs “with a stick,” and being consumed by the pathological grind described earlier. No middle ground exists in this telling. The possibility of critical, limited, or thoughtful engagement with these tools is never acknowledged as legitimate. You are either pure or contaminated.

Reality doesn’t work this way! It’s not black and white. My take: AI is a transformative technology and the spectrum of uses and misuses of AI is vast and growing.

The philosophical core of their argument also contains an unexamined equivocation. The author invokes the extended cognition thesis — the idea that tools become part of us and shape who we are — to make AI seem uniquely threatening. But this same argument applies to every tool mentioned in the piece: hammers, pens, keyboards, dictionaries. The author describes their own fingers “flying over the keyboard, switching windows, opening notes, looking up words in a dictionary” as part of their extended cognitive process. If consulting a dictionary shapes thought and becomes part of our cognitive process, what exactly distinguishes that from asking a language model to check grammar or suggest a word? The author never establishes what makes AI categorically different from the other tools that have already become part of us. The danger is assumed rather than demonstrated.

There is also a genetic fallacy at work in the argument about power. The author suggests AI is bad partly because of who controls it — surveillance capitalists, fascists, those with enormous physical infrastructure. But this argument conflates the origin and ownership of a technology with its inherent properties. One could make identical arguments about the printing press, the telephone, or the internet itself. The question of whether these tools could be structured differently, owned differently, or used toward different ends is never engaged. Everything becomes evidence of a monolithic system of control.

Finally, there is an unacknowledged irony in the piece’s medium and advice. The author recommends spending less time on social media and reading books instead, while writing a blog post clearly designed for social sharing, complete with the vivid metaphors, escalating moral stakes, and calls to action that characterize viral content. The post exists within and depends upon the very attention economy it criticizes. This is not necessarily hypocrisy — we all must operate within systems we find problematic — but the lack of self-awareness about it is notable given how readily the author judges others for their compromises.

The essay is most compelling when it stays concrete: the phenomenology of writing as discovery, the real pressures workers face, the genuine concerns about who controls these systems and toward what ends. It is weakest when it reaches for grand unified theories of intentional domination, when it mistakes assertion for argument, and when it allows moral contempt to override the structural analysis it claims to offer. The author clearly cares about human flourishing and autonomy, but the piece would be stronger if that care extended more generously to those navigating these technologies without the privilege of refusal.

Re: I don't care how well your "AI" works

#237

I get that some people want to be intellectually "pure". Artisans crafting high-quality software, made with love, and all that stuff. But one emerging reality for everyone should be that businesses are swallowing the AI-hype raw. You really need a competent and understanding boss to not be labeled a luddite, because let's be real - LLMs have made everyone more "productive" on paper. Non-coders are churning out small…

> If your org is blindly data/metric driven

Are there for profit companies (not non profits, research institutes etc…) that are not metric driven?

Re: I don't care how well your "AI" works

#239
post #23

And then there is the moderate position: Don't be the person refusing the use a calculator / PC / mobile phone / AI. Regularly give the new tool a chance and check if improvements are useful for specific tasks. And carry on with your life.

The biggest change in my career was when I got promoted to be a linux sysadmin at a large tech company that was moving to AWS. It was my first sysadmin job and I barely knew what I was doing, but I knew some bash and python. I had a chance to learn how to manage stuff in data centers by logging into servers with ssh and running perl scripts, or I could learn cloudformation because that was what management wanted. Everybody else on my team thought AWS was a fad and refused to touch it, unless absolutely forced to. I wrote a ton of terrible cloudformation and chef cookbooks and got promoted twice times and my salary went from $50,000 a year to $150,000 a year in 3 years after I took a job elsewhere. AFAIK, most of the people on that team got laid off when that whole team was eliminated a few years after I left.

Re: I don't care how well your "AI" works

#240

> And yeah, I get it. We programmers are currently living through the devaluation of our craft, in a way and rate we never anticipated possible. I'm a programmer, been coding professionally for 10 something years, and coding for myself longer than that. What are they talking about? What is this "devaluation"? I'm getting paid more than ever for a job I feel like I almost shouldn't get paid for (I'm just having fun),…

> And now, we're having a huge explosion of tools for developers, to build software that has to be maintained by developers, made by developers for developers. What do you think they're building all those datacenters for? Why do you think so much money is pouring into AI companies? It's not to help make developers more efficient with code assistants. Traditional computation will be replaced with bots in every aspect…

I agree with all this, except there is no plan B. What could plan B possibly be when white collar work collapses? You can go into a trade, but who will be hiring the tradespeople?
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