An Overwhelmingly Negative and Demoralizing Force

I'm no big fan of LLM generated code, but the fact that GP bluntly states "AI will never produce a deletion" despite this being categorically false makes it hard to take the rest of their spiel in good faith.

As a side note, I've had coworkers disappear for N days too and in that time the requirements changed (as is our business) and their lack of communication meant that their work was incompatible with the new requirements. So just because someone achieves a 10x speedup in a vacuum also isn't necessarily always a good thing.

I messed around with Copilot for a while and this is one of the things that actually really impressed me. It was very good at taking a messy block of code, and simplifying it by removing unnecessary stuff, sometimes reducing it to a one line lambda. Very helpful!

AI can refactor or trim code. But in practice, the way it's being used and measured in most orgs is all about speed and output

So its rather that AI amplifies the already existing short-term incentives, increasing the harder to attribute and easier to ignore long-term costs.

The one actual major downside to AI is that PM and higher are now looking for problems to solve with it. I haven't really seen this before a lot with technology, except when cloud first became a thing and maybe sometimes with Microsoft products.

This is probably just me projecting...

u/justonceokay's wrote:

> The solution to bad code is more code.

This has always been true, in all domains.

Gen-AI's contribution is further automating the production of "slop". Bots arguing with other bots, perpetuating the vicious cycle of bullshit jobs (David Graeber) and enshitification (Cory Docotrow).

u/justonceokay's wrote:

> AI will never produce a deletion.

I acknowledge your example of tidying up some code. What Bill Joy may have characterized as "working in the small".

But what of novelty, craft, innovation? Can Gen-AI, moot the need for code? Like the oft-cited example of -2,000 LOC? https://www.folklore.org/Negative_2000_Lines_Of_Code.html

Can Gen-AI do the (traditional, pre 2000s) role of quality assurance? Identify unnecessary or unneeded work? Tie functionality back to requirements? Verify the goal has been satisfied?

Not yet, for sure. But I guess it's conceivable, provided sufficient training data. Is there sufficient training data?

You wrote:

> only focus on adding new features

Yup.

Further, somewhere in the transition from shipping CDs to publishing services, I went from developing products to just doing IT & data processing.

The code I write today (in anger) has a shorter shelf-life, creates much less value, is barely even worth the bother of creation much less validation.

Gen-AI can absolutely do all this @!#!$hit IT and data processing monkey motion.

>If you do this you are creating a rod for your own back: You need management to see the failures & the time it takes to fix them, otherwise they will assume everything is fine & wonderful with their new toy & proceed with their plan to inflict it on everyone, oblivious to the true costs + benefits.

If at every company I work for, my manager's average 7-8 months in their role as _my_ manager, and I am switching jobs every 2-3 years because companies would rather rehire their entire staff than give out raises that are even a portion of the market growth, why would I care?

Not that the market is currently in that state, but that's how a large portion of tech companies were operating for the past decade. Long term consequences don't matter because there are no longer term relationships.

Why are you letting the AI construct poorly structured code? You should be discussing an architectural plan with it first and only signing off on the code design when you are comfortable with it.

It feels like LLMs are doing to coding what the internet/attention economy did to journalism.

>>AI use makes the metric for success speed-to-production

> Wasn't it like that always for most companies? Get to market fast, add features fast, sell them, add more features?

This reminds me of an old software engineering adage.

  When delivering a system, there are three choices
  stakeholders have:

  You can have it fast,
  You can have it cheap,
  You can have it correct.

  Pick any two.

Is because unlike prior hype cycles, this one is super easy for an MBA to point at and sort of see a way to integrate it.

Prior hype, like block chain are more abstract, therefore less useful to people who understand managing but not the actual work.

Automation of knowledge work. Simply by using AI you are training your own replacement and integrating it into company processes.

Rather than some conspiracy, my suspicion is that AI companies accidentally succeded in building a machine capable of hacking (some) people's brains. Not because it's superhumanly intelligent, or even has any agenda at all, but simply because LLMs are specifically tuned to generate the kind of language that is convincing to the "average person".

Managers and politicians might be especially susceptible to this, but there's also enough in the tech crowd who seem to have been hypnotized into becoming mindless enthusiasts for AI.

Recommending that someone in the industry take pointers from how students do their work is always solid advice.

I'm taking a course on computational health laboratory. I do have to say gemini is helping me a lot, but someone who knows what's happening is going to be much better than us. Our professor told us it is of course allowed to make things with llms, since on the field we will be able to do that. However, I found they're much less precise with bio-informatic libraries than others...

I do have to say that we're just approaching the tip of the iceberg and there are huge issues related to standardization, dirty datas... We still need the supervision and the help of one of the two professors to proceed even with llms

I have general one-shot success asking chatgpt to make bash/python scripts and one-liners where otherwise it would take 1hr to a day to figure out on my own (and I'd use one of my main languages maybe) or I might not even bother trying, which is great for productivity but also over 90% of my job doesn't need throw-away scripts and one-liners.

Our org seems to be taking some benefits from being sped up by using AI tools for code generation (much of it is CRUD or layout stuff), however at times I'm asked for help by colleagues and the first thing I've done is Googled and found the answer and gotten a "Oh right, you can google also" since they've been trying to figure out the issue with ChatGPT or similar.

That’s such outdated thinking. I’m using AI to build AI into my workflows.

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> People like that will always be more effective at their job once employed

This is honestly not my experience with self taught programmers. They can produce excellent code in a vacuum but they often lack a ton of foundational stuff

In a past job, I had to untangle a massive nested loop structure written by a self taught dev, which did work but ran extremely slowly

He was very confused and asked me to explain why my code ran fast, his ran slow, because "it was the same number of loops"

I tried to explain Big O, linear versus exponential complexity, etc, but he really didn't get it

But the company was very impressed by him and considered him our "rockstar" because he produced high volumes of code very quickly

GP didn't mention university degrees.

You get experienced devs from inexperienced devs that get experience.

[edit: added "degrees" as intended. University was mentioned as the context of their observation]

> There will always be individuals that enjoy coding and do so without any formal teaching.

We're talking about the industry responsible for ALL the growth of the largest economy in the history of the world. It's not the 1970s anymore. You can't just count on weirdos in basements to build an industry.

> There will always be individuals that enjoy coding and do so without any formal teaching.

That's not the kind of experience companies look for though. Do you have a degree? How much time have you spent working for other companies? That's all that matters to them.

> criticizing the humans that are using AI to replace workers, instead of criticizing AI itself

I think you misunderstand OP's point. An employer saying "we only hire experienced developers [therefore worries about inexperienced developers being misled by AI are unlikely to manifest]" doesn't seem to realize that the AI is what makes inexperienced developers. In particular, using the AI to learn the craft will not allow prospective developers to learn the fundamentals that will help them understand when the AI is being unhelpful.

It's not so much to do with roles currently being performed by humans instead being performed by AI. It's that the experienced humans (engineers, doctors, lawyers, researchers, etc.) who can benefit the most from AI will eventually retire and the inexperienced humans who don't benefit much from AI will be shit outta luck because the adults in the room didn't think they'd need an actual education.

Actually, there are two main problems with AI:

    1. How it's gonna be used and how it'll be a detriment to quality and knowledge.
    2. How AI models are trained with a great disregard to consent, ethics, and licenses.

... smells very similar to tobacco/soda industry. Both created faux-research institutes to further their causes.

> Almost every time I hear this argument, I realize that people are not actually complaining about AI, but about how modern capitalism is going to use AI.

This was pretty consistently my and many others viewpoint since 2023. We were assured many times over that this time it would be different. I found this unconvincing.

i don't think it's an either/or situation

> I realize that people are not actually complaining about AI, but about how modern capitalism is going to use AI.

Something very similar can be said about the issue of guns in America. We live in a profoundly sick society where the airwaves fill our ears with fear, envy and hatred. The easy availability of guns might not have been a problem if it didn't intersect with a zero-sum economy.

Couple that with the unavailability of community and social supports and you have a a recipe for disaster.

Like TikTok AI Coding breaks human psychology. It is engrained in us that if we have a tool that looks right enough and highly productive we will over-apply it to our work. Even diligent programmers will be lured to accepting giant commits without diligent review and they will pay for it.

Of course yeeting bad code into production with a poor review process is already a thing. But this will scale that bad code as now you have developers who will have grown up on it.

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But make some shallow games with generic, cell-shaded anime waifus accessed by gambling and they eat that shit up

It's not so much optimism as facts. Large AAA game companies have driven away investors[0] and talent[1]. The old growth engines (microtransactions, live service games, season passes, user-generated content, loot boxes, eSports hero shooters, etc.) also no longer work, as neither general players nor whales find them appealing.

AI is considered a potential future growth engine, as it cuts costs in art production, where the bulk of game production costs lie. Game executives are latching onto it hard because it's arguably one of the few straightforward ways to keep growing their publicly-traded companies and their own stock earnings. But technologists already know how this will end.

Other games industry leaders are betting on collapse and renewal to simpler business models, like self-funded value-first games. Also, many bet on less cashflow-intensive game production, including lower salaries (there is much to be said about that).

Looking at industry reports and business circle murmurs, this is the current state of gaming. Some consider it optimistic, and others (especially the business types without much creative talent) - dire. But it does seem to be the objective situation.

[0] VC investment has been down by more than 10x over the last two years, and many big Western game companies have lost investors' money in the previous five years. See Matthew Ball's report, which I linked in my parent comment, for more info.

[1] The games industry has seen more than 10% sustained attrition over the last 5 years, and about 50% of employees hope to leave their employer within a year: https://www.skillsearch.com/news/item/games---interactive-sa...

Not to mention the variations of "you need to prompt better" including now "rules files" which begs the question: wouldn't just writing code be a much better way to exercise control over the machine?

The same can be said about the other side. It is rarely phrased has "LLM is a useful tool with some important limitations" but "Look the LLM manage to create a junior-level feature, therefor we won't need developers in 2 years from now".

It tends to be the same with anything hyped / divisive. Human tend to exaggerate in both direction in communication, especially in low-stake environment such as an internet forum, or when they stand to gain something from the hype.

You seem to have confused "The whole AI thing is nonsense. [Anecdote]." with "The whole AI thing is nonsense because [anecdote]." I see a lot of "LLMs are not useful. e.g. the other day I asked it to do X and it was terrible." That is not somebody saying that that one experience definitively proves that LLMs are useless, or saying that you should believe that LLMs are useful based only on that one anecdote. It is people making their posts more interesting than just giving their opinions along with arguments for those opinions.

Obviously their views are based on the sum of all their experience with LLMs. We don't have to say so every time.