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PaperclipPerfector  4d ago (text post)   23011 thread views

Culture War Roundup for the week of June 9, 2025

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As somone who's been working in the field of machine learning since 2012 and generally agrees with @SubstantialFrivolity's assesment, I think that what we are looking here is a bifurcation in opinion between people looking for "bouba" solutions and those looking for "kiki" solutions.

If you're a high-school student or literature major with zero background in computer science looking to build a website or develop baby's first mobile app LLM generated code is a complete game changer. Literally the best thing since sliced bread. (The OP, and @self_made_human's comments reflect this)

If you're a decently competent programmer at a big tech firm, LLMs are at best a mild productivity booster. (See @kky's comments below)

If you are decently competent programmer working in an industry where things like accuracy, precision, and security are core concerns, LLMs start to look anti-productive as in the time you spent messing around with prompts, checking the LLM's work, and correcting it's errors, you could've easily done the work yourself.

Finally if you're one of those dark wizards working in FORTRAN or some proprietary machine language because this is Sparta IBM/Nvidia/TMSC and the compute must flow, you're skeptical of the claim that an LLM can write code that would compile at all.

If you are decently competent programmer working in an industry where things like accuracy, precision, and security are core concerns, LLMs start to look anti-productive as in the time you spent messing around with prompts, checking the LLM's work, and correcting it's errors, you could've easily done the work yourself.

I think this fairly nicely summarizes how I feel. Not that I do work in one of those industries to be fair, but it's part of my personal work ethic I guess you might say. I want computers (and programs) to be correct first and foremost. Speed or ease of development don't mean much to me if the result can't be relied upon. Not only that, I want my tools to be correct first and foremost. I wouldn't accept a hammer where the head randomly fell off the handle 10% of the time or even 1% of the time. So I similarly have very little patience for an LLM which is inherently going to make mistakes in non-deterministic ways.

Preach, brother. Software is made to be clear and predictable. Learning to make it that way, one line at a time, is our craft. You can always tell the brilliant programmer apart because 99% of that code is simple as can be and 1% is commented like a formal proof. Worse than LLMs, reliance on LLMs risks undermining this skill. Who can say if something is correct if the justification is just that it came from the machine? There needs to be an external standard by which code is validated, and it must be internalized by humans so they can judge.

If you're a high-school student or literature major with zero background in computer science looking to build a website or develop baby's first mobile app LLM generated code is a complete game changer. Literally the best thing since sliced bread.

You have to contend with the fact that like 95+% of employed programmers are at this level for this whole thing to click into place. It can write full stack CRUD code easily and consistently. five years ago you could have walked into any bank in any of the top 20 major cities in the united states with the coding ability of o3 and some basic soft skills and be earning six figures within 5 years. I know this to be the case, I've trained and hired these people.

If you are decently competent programmer working in an industry where things like accuracy, precision, and security are core concerns, LLMs start to look anti-productive as in the time you spent messing around with prompts, checking the LLM's work, and correcting it's errors, you could've easily done the work yourself.

I did allude that there might be a level of programming where one needs to see through the matrix to do but in SF's post and in most situations I've heard the critique in it's not really the case. They're just using it for writing config files that are annoying because they pull together a bunch of confusing contexts and interface with proprietary systems that you need to basically learn from institutional knowledge. The thing LLMs are worst at. Infrastructure and configuration are the two things most programmers hate the most because it's not really the more fulfilling code parts. But AI is good at the fulfilling code parts for the same reason people like doing them.

In time LLMs will be baked into the infrastructure parts too because it really is just a matter of context and standardization. It's not a capabilities problem, just a situation where context is splined between different systems.

Finally if you're one of those dark wizards working in FORTRAN or some proprietary machine language because this is Sparta IBM/Nvidia/TMSC and the compute must flow, you're skeptical of the claim that an LLM can write code that would compile at all.

If anything this is reversed, it can write FORTRAN fine, it probably can't do it in the proprietary hacked together nonsense installations put together in the 80s by people working in a time where patterns came on printed paper and might collaborate on standards once a year at a conference if they were all stars. but that's not the bot's fault. This is the kind of thinking that is impressed by calculators because it doesn't properly understand what's hard about some things.

I feel like I'm taking crazy pills here. No one's examples about how it can't write code are about it writing code. It's all config files and vague evals. No one is talking about it's ability to write code. It's all devops stuff.

This is the kind of thinking that is impressed by calculators because it doesn't properly understand what's hard about some things.

Ironically I considered saying almost this exact thing in my above comment, but scratched it out as too antagonistic.

The high-school students and literature majors are impressed by LLMs ability to write code because they do not know enough about coding to know what parts are easy and what parts are hard.

Writing something that looks like netcode and maybe even compiles/runs is easy. (All you need is a socket, a for loop, a few if statements, a return case, and you're done) Writing netcode that is stable, functional, and secure enough to pass muster in the banking industry is hard. This is what i was gesturing towards with "Bouba" vs "Kiki" distinction. Banks are notoriously "prickly" about thier code because banking (unlike most of what Facebook, Amazon, and Google do) is one of those industries where the accuracy and security of information are core concerns.

Finally which LLM are you using to write FORTRAN? because after some brief experimentation niether Gemini nor Claude are anywhere close.

What do you imagine is the ratio just at banks between people writing performant net code and people writing crud apps? If you want to be an elitist about it then be my guest, but it's a completely insane standard. Honestly the people rolling out the internal llm tooling almost certainly outnumber the people doing the work you're describing.

I do not think that expecting basic competency is an "insane standard" or even that elitist. Stop making excuses for sub-par work and answer the question.

Which LLM are you using to write FORTRAN?

What sort of problem did you ask it to solve?

In your effort to declare LLMs as incapable programmers you're excluding 95%+ of the profession, not literature majors. not high school students. Professional programers with CS and SE degrees. All I've been asking is for you to acknowledge that. If your standard is quant on a hft desk then great for you. I'm sure you're an excellent programmer. You'll probably have a job for six months longer than me.

Are you trying to Bugs Bunny me?

You're the one who made the claim that 95%+ of employed programmers were literature majors with no background in computer science, not me.

The level of skill where LLMs are immediately useful, not the literature background. Obviously 95% of programmers don't have a literature background.

I mean, my full opinion and experience with LLMs is much harsher than my comment suggested, but I don’t want to start fights with enjoyers on the net. (At least, not this time.) Chances are their circumstances are different. But I would be seriously offended if someone sent me AI-generated code in my main area of expertise because it would be subtly or blatantly wrong and be a serious waste of my time trying to figure out all the errors of logic which only become apparent if you understand the implicit contracts involved in the domain. Goodness knows it’s bad enough when merely inexperienced programmers ask for review without first asking advice on how to approach the problem, or even without serious testing…

Goodness knows it’s bad enough when merely inexperienced programmers ask for review without first asking advice on how to approach the problem, or even without serious testing…

I know that pain.

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