[QuantumNomad_]

People in the future are going to wonder what the hell we were thinking, when 30 years down the line everything is a hot mess of billions of lines of code generated by LLMs that no human has read almost any of it and is no longer possible for anyone to maintain neither with nor without LLMs. And the LLM generated garbage will have drowned out all of the good quality code that ever existed and no one will be able to find even human generated code anymore on the internet.

Makes me want to just give up programming forever and never use a computer again.

[pllbnk]

I think it’s a mistake to think that we will be blindly going in this direction for many years and then suddenly collectively wake up and realize what have we done. It’s a great filter and a great opportunity.

If LLMs stop improving at the pace of the last few years (I believe they already are slowing down) then they will still manage to crank out billions lines of code which they themselves won’t be able to grep and reason through, leading to drop in quality and lost revenue for the companies that choose to go all-in with LLMs.

But let’s be realistic - modern LLMs are still a great and useful tool when used properly so they will stay. Our goal will be to keep them on track and reduce the negative impact of hallucinations.

As a result software industry will move away from large complex interconnected systems that have millions of features but only a few of them actively used, to small high quality targeted tools. Because their work will be easier to verify and to control the side effects.

[leptons]

I wish I got to hallucinate at work, and just get a pat on the head for constantly doing the wrong thing.

[pllbnk]

Maybe I am unlucky but I had worked with too many developers who couldn't make a good decision if their life depended on it. LLMs at least know how to convince you of their decisions with strong arguments.

[nothinkjustai]

Mmm, I feel it’s more common for them to just blindly agree with whatever you say.

Assistant: “I propose A”

User: “Actually B is better”

Assistant: “you’re absolutely right”

User: “actually let’s go with C”

Assistant: “Good choice, reasons”

User: “wait A is better”

Assistant: “Great decision!”

[oompydoompy74]

The title for that is Director, VP, or CTO at any given large enterprise company.

[leptons]

People downvoted you, but I actually know a few of these people.

[2ndorderthought]

I mean you can do that, but the job probably doesn't pay too much. Might enrich your spirituality though.

[lelanthran]

> If LLMs stop improving at the pace of the last few years (I believe they already are slowing down)

Depending on how you measure "improvement" they already have or they never will :-/

Measuring capability of the model as a ratio of context length, you reach the limits at around 300k-400k tokens of context; after that you have diminishing returns. We passed this point.

Measuring capability purely by output, smarter harnesses in the future may unlock even more improvements in outputs; basically a twist on the "Sufficiently Smart Compiler" (https://wiki.c2.com/?SufficientlySmartCompiler=)

That's the two extremes but there's more on the spectrum in between.

[rgbrenner]

300k-400k isn’t the current limit if you create modules and/or organize the code reasonably.. for the same reason we do this for humans: it allows us to interact with a component without loading the internals into out context.

you can also execute larger tasks than this using subagents to divide the work so each segment doesn’t exceed the usable context window. i regular execute tasks that require hundreds of subagents, for example.

in practice the context window is effectively unlimited or at least exceptionally high — 100m+ tokens. it just requires you to structure the work so it can be done effectively — not so dissimilar to what you would do for a person

[jmalicki]

That makes it not a context window.

How to organize code like you said, and how agents interact with it, to keep the actual context window small is the fundamental challenge.

[lelanthran]

I keep getting surprised that people who are all-in on this (" i regular execute tasks that require hundreds of subagents ") don't have any idea of what is happening even a single layer below their interface to the LLM ("in practice the context window is effectively unlimited or at least exceptionally high — 100m+ tokens.")

I looked at that response by GP (rgbrenner) and refrained from replying because if someone is both running hundreds of agents at a time AND oblivious to what "context window" means, there is no possible sane discourse that would result from any engagement.

[rgbrenner]

ok "series of context windows spread across many agents".. sure much clearer.

Doesn't change my point: the amount of code the agent can operate on is very large, if not unlimited, as long as you put even a little bit of thought into structuring things so it can be divided along a boundary.

If you let the codebase degrade into spaghetti, then the LLM is going to have the same problem any engineer would have with that. The rules for good code didn't disappear.

[jmalicki]

Context windows don't necessarily cleanly divide. Getting each agent to be able to task within a context window is a hard problem.

It's like like if your context window with one agent is n, your context window with 10 agents is n/10. It is some skill, but that is also where a lot of the advances are coming in.

[parliament32]

> I believe they already are slowing down

They certainly have. The only impactful improvement in the last year is "just run it in a loop until it gets it right" lmao

Which, of course, only works as long as the costs are subsidized by the companies vying for market share.

[ilaksh]

30 years down the line a human will wake up in his climate controlled bed in an idyllic large scale people-zoo, think about what information he wants, and immediately his 900TB ferroelectric compute-in-memory exobrain will read his thoughts via his brain-computer-interface, and render a custom 3d visualization of that information floating in front of him. There will be no separate code stage, just neural rendering of data to pixels.

[efnx]

Better not think a forbidden thought. Oh shoot! You just did! :)

[frizlab]

Well thanks, I lost the game now :|

[giraffe_lady]

Who empties the bedpan?

[sunrunner]

It's a tube and it's directly connected, for efficiency. Feel free to fill in the rest of the story.

[sunrunner]

> custom 3d visualization of that information floating in front of him.

Eh, what a waste. Can't we just stimulate the optic nerve? Or better yet, whatever region of the brain is responsible for me being able to 'see' anything? And perhaps we can finally get smell-o-vision too.

[ilaksh]

I was hoping that the visuals going through the BCI also was implied since I didn't indicate any other new technology for holograms.

[butlike]

But are the pixels hot?

[jf22]

First, most software is already a hot mess.

Second, LLM code can be less of a hot mess than human written code if you put in the time to train/prompt/verify/review.

Generating perfect well patterned SOLID and unit tested code with no warnings or anti-patterns has never been easier.

[yakattak]

The only people who are going to put in the time, are people who care enough to. The problem is you have people who didn’t care before who were equipped with a garden hose. Now that they have a fully pressurized fire hose they can make more of a mess faster.

[risyachka]

This is so on point that I want to cry.

[senordevnyc]

Then they should be easy to defeat. Why are you complaining?

[themgt]

As an author of fine literature, these million monkeys on typewriters simply upset my sense of dignity. And to imagine the impoverished prose so many readers shalt forthwith be perusing!

[yakattak]

Defeat in what aspect?

[senordevnyc]

Compete with, for jobs, customers, investment, etc.

[yakattak]

Maybe. But it depends on the metric. It seems like orgs are focused on PR count and token usage. Issues caused by poor code are often lagging indicators so it’s asymmetrical in that aspect.

Write lots of code now and statistically look great, while the impact won’t be felt for a much larger range of time.

With the job search and whatnot then yeah, caring becomes a lot more important. That’s true.

[Daishiman]

Hard disagree. LLMs are fantastic for fixing bad architecture that's been around for a decade because nobody was willing to touch it. I can have it write tons and tons of sanity checks and then have it rewrite functionality piece by piece with far more verification than what I'd get from most engineers.

It's not immediate, it still takes weeks if you want to actually do QA and roll out to prod, but it's definitely better than the pre-LLM alternatives.

[yakattak]

Yeah but you care which is my exact point.

[Daishiman]

How is this different from every single technological iteration?

[salawat]

Because there is a certain point where barrier to entry prevents meaningful competition once winner-take-all power laws start kicking in, and stability hitherto has been predisposed on having a plurality of non interrelated competitors to ensure no one man's quirks drives too much of societies theoretical output.

AI will make this dynamic worse, and it's got the extra danger of the default banal way of applying the technology in fact encourages it's application to that end.

[jplusequalt]

>First, most software is already a hot mess.

That the industry was already routinely dealing with fires of it's own creation is not a valid reason to start cooking with gasoline.

[jf22]

But we aren't cooking with gas. We are cooking with a more controlled burner than ever that can download a clean code claude skill and be committing better code than you or I could write.

What would normally be considered overengineered gold plating is "free" now.

[switchbak]

Like with a lot of things in this space, it depends where you invest your effort. If you care about quality design and good code, you can definitely get there - but that doesn't happen by default.

With the right investment, we could certainly have tooling that creates and maintains very good designs out of the box. My bet is that we'll continue chasing quick and hacky code, mostly because that's the majority of the code that it was trained on, and because the majority of people seem to be interested in a quick result vs a long-term maintainable one.

[glouwbug]

Right, but it takes one to know one. Many don’t have the ability to decipher what’s good stable output or not

[ativzzz]

By then, the fix will be easy. Fire up the latest LLM, point it at your codebase and tell it "rewrite this from scratch. do it well. fix the architecture mistakes"

[jcalx]

There is definitely going to be some Wirth's law-like [0] effect about the asymmetry of software complexity outpacing LLMs' abilities to untangle said software. Claude 9.2 Optimus Prime might be able to wrangle 1M LoC, but somehow YC 2035 will have some Series A startup with 1B+ LoC in prod — we'll always have software companies teetering on the very edge of unmaintainability.

[0] https://en.wikipedia.org/wiki/Wirth%27s_law

[AlotOfReading]

It's the Peter principle for computers. Codebases expand to the limits of the organization's ability to manage them. If you make one person use ed to write code for a bare metal environment, you'll get a comparatively small, laser-focused codebase. If you task a hundred modern developers to solve the same problem, you'll get a Linux box device running a million lines of JavaScript.

Same thing happens in other fields. A rich country and a poor country might build equivalent roads, but they won't pay the same price for them.

[faizshah]

It won't be an LLM that does it, the entire feature of an LLM is it produces generalizable reasonably "correct" text in response to a context.

The system that makes it have an opinion about good vs bad architecture or engineering sensibilities will be something on top of the transformer and probably something more deterministic than a prompt.

[hasbot]

We can do this today too (but definitely hopefully future LLMs make better architectural decisions). With Claude, I've been working on an application for the last 2 months. I didn't have a great vision of what I wanted when I started but I didn't want that to slow me down. The architecture is terrible - Claude separated some functionality into different classes but did a bad job at it and created a big ball of mud. Now that I finally have my vision locked down and implemented (albeit poorly), it'd be a great time to throw it away and start over. It'd be interesting to see the result and see how long it takes.

[ativzzz]

Just have claude (or gpt maybe) do an architecture review and request a multi-phase refactoring plan. This is probably better to do incrementally as you notice the balls of mud forming but it might not be too late. Either way, if it does something you don't like, `git checkout` and start over

[bulbar]

Will work just as good as today or 20 years ago.

[cortesoft]

Are you suggesting AI coding was as good 20 years ago as it is today?

[hrldcpr]

I think they're being sarcastic, saying that rewrites from scratch have rarely worked well (whether done by AI or humans).

[bulbar]

Exactly. Sorry for not being explicit about it. I thought it was clear enough, because 'this code is crap, let's just rewrite the whole thing, doesn't look to hard' is kind of famous for being a bad idea most of the time since forever.

[vrganj]

It sure wrote less crappy code.

[fnoef]

"Make sure to double check everything, and MAKE NO MISTAKES!!!"

[unfunco]

Don't hallucinate!

[bhagyeshsp]

"YOU'RE A SENIOR SOFTWARE ENGINEER!!!"

[ryandrake]

"Ultrathink!"

[kurthr]

"Write me a really cool game, that will make me lots of money, fast!"

[KumaBear]

Make me a 1hr episode of my favorite book. Make it as lore accurate as possible. Plot out the script for the next 100 episodes.

[estimator7292]

I see your point, however: EA sports has been doing this for literally the entire lifetime of gaming as an industry

[DonHopkins]

Electronic Sharts slogans and franchises:

"Shit's in the Game!"

"Chunder Everything"

"Maddening NFL 26"

"FIFiAsco 26"

"UFC 26 (Un Finished Code)"

"The Shits 4"

"Battlefailed"

"Need for Greed"

[orphea]

Do you think new LLMs are going to write better and better code? When all they are going to have is the slop generated by previous, worse models?

[chickensong]

Yes. The models may have started from indiscriminate scraping, but people are undoubtedly working on refining the training data. Combined with the overall model capabilities, I suspect code quality will continue to go up.

What you're suggesting is a negative flywheel where quality spirals down, but I'm hoping it becomes a positive loop and the quality floor goes up. We had plenty of slop before LLMs, and not all LLM output is slop. Time will tell, but I think LLMs will continue to improve their coding abilities and push overall quality higher.

[orphea]

Let's agree to disagree.

What I see is that while LLMs can do real tasks, they often produce overengineered unmaintainable slop (plenty of examples where code can be reduced 10x to do the same). I hope this is not a base to continue training LLMs on.

[chickensong]

I don't disagree that there's a lot of slop getting churned out, you're not wrong there. I just have hopes that we'll course-correct after some initial adjustment period, but I have no idea how long that might be (guessing several years).

I don't know how long LLMs will hold their position, but in my mind, it makes sense that computers will eventually be the best programmers. Humans will still guide, but rarely write or even read code. I might be dead by then, but that's my prediction for the future.

[genghisjahn]

I'm generally pro "llm assisted coding" or whatever you want to call it. But I do somethings think about the Butlerian Jihad from Dune.

https://en.wikipedia.org/wiki/Dune:_The_Butlerian_Jihad

[hermitShell]

If you like sci-fi takes on software systems, check out Vernor Vinge "A Fire upon the deep" and sequels. I recall ship systems software is something like all the code humanity has ever written, plus centuries of LLM churn. One of the protagonists is a space faring software developer particularly good with legacy code.

We are used to thinking about software like in the article, a program that runs deterministically in an OS. Where we are headed might be more like where the LLM or AI system is the OS, and accomplishes things we want through a combination of pre-written legacy software, and perhaps able to accomplish new things on the fly.

[genghisjahn]

Interesting, I kinda do this. Sometimes when an LLM solves a problem for me, I have it write code so that I can reuse that exact same approach deterministically(and I line by line check it). Now I have about a dozen CLI commands that the LLM can use and I'm reasonably (although not 100%) sure I'll get an expected outcome. Really helpful with debugging via steam pipe and connecting to read replicas.

[DonHopkins]

Pham Nuwen is a master of vibe patching legacy sedimentary software.

[Izkata]

Sounds like a recipe for Star Trek holodeck malfunctions.

[genghisjahn]

Ordered Fire Upon the Deep. Looks interesting.

[michelb]

If 30 years down the line I still have to look at code, maintain code, or even worry in the slightest about code, something went deeply wrong.

[skydhash]

Code will never go away. Code was there before computer hardware and it will always be there. Code is (almost?) all of computation theory so unless we throw computers away, we shall always use code.

[phainopepla2]

They're not suggesting that code will go away, but rather that it will be abstracted beneath an LLM interface, so that writing code in the future will be like writing assembly today: some people do it for fun or niche reasons, but otherwise it's not necessary, and most developers can't do it.

Whether that happens or not is a different question, but I believe that's what they're suggesting.

[skydhash]

Code is formal and there are basic axioms that grounds its semantic. You can build great constructs on top of those semantics, but you can’t strip away their formality without the whole thing being meaningless. And if you can formalize a statement well enough to remove all ambiguity, then it will turn into code.

Programming is taking ambiguous specs and turning them into formal programs. It’s clerical work, taking each terms of the specs and each statements, ensuring that they have a single definition and then write that definition with a programming language. The hard work here is finding that definition and ensuring that it’s singular across the specs.

Software Engineering is ensuring that programming is sustainable. Specs rarely stay static and are often full of unknowns. So you research those unknowns and try to keep the cost of changing the code (to match the new version of the specs) low. The former is where I spend the majority of my time. The latter is why I write code that not necessary right now or in a way that doesn’t matter to the computer so that I can be flexible in the future.

While both activities are closely related, they’re not the same. Using LLM to formalize statements is gambling. And if your statement is already formal, what you want is a DSL or a library. Using LLM for research can help, but mostly as a stepping stone for the real research (to eliminate hallucinations).

[Keyframe]

Why are we pretending everyone's code is an etalon of quality? Most software out there is probably hot mess already. No think behind it, let alone ultrathink.

[Maxatar]

Exactly, before the rise of LLMs it was not at all uncommon to hear people claiming that their job is to just Google API calls or copy and paste code from Stackoverflow. The context back then was that companies are being picky by hiring people who can demonstrate some modicum of understanding of data structures and algorithms because all any developer does is tweak some CSS or make some calls to a database to glue together a CRUD app... why should anyone be expected to know how to reverse a linked list, or how a basic sorting algorithm works... just download an npm package to do that stuff and glue it all together with a series of nested for loops.

With the rise of LLMs that do all of that... those people shutup and shutup real fast.

[murukesh_s]

Hello from assembly programmers to present day javascript folks. Joke aside, I sometimes think how VS Code is written in such layers and layers of code - ~200mb of minified code - Java based IDEs were worser with almost 1GB of code (libs/dependencies). And VS Code did beat native editors (Sublime) of its time to dominate now - may be because of the business model (open & free vs freemium). But it does the job quite well IMO. And it enabled swarms of startups to go to market including billion $ wrappers - including Cursor, Antigravity and almost all UI coding agents. I remember backend developers (Java/C++ type) looking down upon Javascript developers as if we are from an inferior planet or something.

How many of us remember that VSCode is actually a browser wrapped inside a native frame?

[skydhash]

VS Code has two things that worked well for it. Web Tech and Money. Web tech makes it easy to write plugins (you already know the stack vs learning python for sublime). And I wonder how much traction it would get if not Microsoft paying devs to wrangle Electron in a usable shape.

[k__]

To be fair, MS send a world class engineer to make JavaScript usable for codebases at that scale.

[000000000001]

>How many of us remember that VSCode is actually a browser wrapped inside a native frame?

The new standard, Web Apps. Why update 3 seperate binaries for Win/Lin/Mac when you can do 1 for a web framework and call it a day?

[pkulak]

I can't get used to vibe-coded projects on Github. One that I was using for a little while is about a year old, with 40,000 commits and 15,000 PRs. And it has "lite" in its name; it's supposed to be the simple alternative. There were so many bugs. I fixed one, submitted a PR, but it was off the first page in hours. It will never be merged. I moved to a different project with a bit less... velocity, and it has been way smoother.

[stronglikedan]

> is no longer possible for anyone to maintain neither with nor without LLMs.

That's what the Tech-Priests are for.

[ofjcihen]

<INTERROGATIVE-HAVE YOU TRIED APPLYING INCENSE AND RECITING THE SACRED TECH LITANIES?>

[johnbarron]

There is nothing in the post to support the statement. An interesting personal confession, but it does not establish that vibe coding and agentic engineering are converging as a general phenomenon.

As a piece of meat, I look forward to charge rates of $10,000 an hour, to fix code out the vibe code generation.

[butlike]

People, as a rule, don't really "go backwards." We didn't really walk back on the industrial revolution, and we're probably not going to walk back from this day-and-age's activities. It's only unsettling until the changes are accepted. The old timers can vie for a time before "all this" when they were children and all their needs were given to them by their now-deceased parents, and the cycle can continue on, yet again.

[throw_this_one]

Why does it matter, as long as it accomplishes the task?

[jimmyjazz14]

If that is the case market forces would likely favor hand written code and all the slop will be forgotten (unless the slop works fine and is stable).

[xantronix]

The market is hardly as rational as people would like to hope it is, though it does at least have its own twisted sort of internal consistency.

[lbrito]

I don't think that's how money works. Enough people have poured enough money into this thing that the actual, measurable results/efficacy/ROI are of secondary importance (to put it mildly). At this point AI adoption is (at least sold as) a fait accompli.

[demorro]

Absurd. Market forces don't optimize for quality, reliability or human welfare. This is religious thinking.

[devin]

This is wishful thinking. The force of the market is "number go up". Quality increasingly has less and less of a role in the equation. You will eat your slop, and you will like it. It will be the only choice you have.

[sesky]

But the quality of code was already very bad due to market forces. Most code at large companies is notoriously poor despite the talent density, because the incentives are not there to tackle tech debt or improve code quality.

With such a low baseline, there is an optimistic perspective that LLMs could improve the situation. LLMs can produce excellent code when prompted or reviewed well. Unlike human employees, the model does not worry about getting a 'partially meets expectations' rating or avoid the drudgery of cleaning up other people's code.

[devin]

The model is optimized in a different way to "partially meet expectations". Sycophancy coupled with only really "knowing" what it has been trained on assure a different kind of mediocrity.

[switchbak]

The same incentives that discourage good code in pre-AI times are still dominating now. You will be pushed to ship sub-par products in the future, just like you were in the past.

AI certainly has the potential to make the underlying code/design a lot cleaner. We will also be working with dramatically more code, at a much higher rate of change. That alone will be a big challenge to keep sustainable.

The ones making the decision to under-invest on design are either are unaware of the real costs, or are aware and are deliberately choosing that path - that's not new, and I don't expect it to change.

[demorro]

The only thing that has changed is that there used to be a loose correlation between capability to effect change and inherent desire for quality. This correlation barely exists anymore, so the counter-cultural acts that happened to manifest quality inside our perverse systems will occur much more rarely now.

[tyyyy3]

I agree generally but there are periods where creative people show up and a whole slew of existing firms go bust/shrink due to one’s ability to envision a path toward creative destruction.

[MagicMoonlight]

Have you seen Windows? We already have thirty years of slop.

[empath75]

> People in the future are going to wonder what the hell we were thinking, when 30 years down the line everything is a hot mess of billions of lines of code generated by LLMs that no human has read

--

It's just as likely that people will be surprised that we used to have billions of lines of human generated code, that no LLM ever approved.

[zuzululu]

By then AI would be good enough to clean them all up....like I dont get these dooming scenarios they always assume that we are going to be stuck with LLMs and there wont be anything new coming.

[orphea]

  By then AI would be good enough to clean them all up...

[citation needed]

To make my comment more on-topic: why do you think this is going to be the case? What newer LLMs will be trained on?

[zuzululu]

well you are assuming that there's not going to be any new progress and that we are going to be stuck with whatever LLM version we have currently

[orphea]

No. I assume that

* we're already close to the ceiling of LLM capabilities: LLM providers probably already consumed everything they could. Plus there have been no large improvements for a while, only small and incremental. I believe Mythos-too-dangerous-to-release is a marketing bullshit, until proved otherwise.

* people generate overengineered slop at light speeds. If that is the training base for future models, I doubt they're going to improve significantly, rather quality is going to stagnate at best.

[beAbU]

Have you ever worked on a legacy codebase with actual good code? I struggle to see the difference between your predicted future and today's reality when it comes to working with legacy disasters.

[jeromegv]

Well, on legacy code base, you still needed humans to write those lines of code. There's a maximal amount of lines a human can write in a year.

Now with LLM we are talking of millions and millions of line of code that could be generated in a single day. The scale of the problem might not be the same at all.

[cj]

> Makes me want to just give up programming forever and never use a computer again.

LLMs aren’t the first thing to come along and change how people develop applications.

You had the rise of frameworks like Django, Rails, etc. Also the rise of SPAs. And also the rise of JS as a frontend+backend language.

In a 3-5 yeats we’ll have adapted to the new norm like we have in the past

[lbrito]

The difference between writing assembly code and Ruby code is much smaller than the difference between programming and vibe coding.

Also, companies are pressuring employees towards adoption in novel ways. There was no such industry-wide pressure by employers in the 90s, 2000s or 2010s for engineers to use a specific tech.

[Daishiman]

> Also, companies are pressuring employees towards adoption in novel ways. There was no such industry-wide pressure by employers in the 90s, 2000s or 2010s for engineers to use a specific tech.

Companies have been enforcing technology mandates since time immemorial. In the early 2000s there were definitely a lot of mandates to move away from commercial UNIX to Linux. Lots of companies began enforcing the switch to PHP, Ruby and Python for new projects.

[lbrito]

Yes, but the entire industry was not pushing any one single tool at the same time. If you disliked Django, you could go to Rails. If you disliked Rails, you had Phoenix. Etc.

Good luck disliking LLM babysitting these days

[toraway]

Or, it could be like asbestos and the immediate benefits are just too appealing to listen to arguments of skeptical naysayers about some vaguely defined problems that are decades away, if they even happen.

I use AI tools daily (because they feel like they're helping me) but it's not exactly hard to imagine scenarios where an explosion of slop piling up plus harm to learning by outsourcing all thinking results in systemic damage that actually slows the pace of technological progress given enough time.

History of new technologies tend to average into a positive trend over a long enough time scale but that doesn't mean there aren't individual ups and downs. Including WTF moments looking back at what now seems like baffling decision-making with benefit of hindsight.

[Izkata]

Some of us are already experiencing that. For example I handed off an initial version of something some months ago, and the AI-generated stuff they came up with was a huge buggy mess of spaghetti code neither of us understood. Months later we've detangled it, cutting it down to a third the size, making it far simpler to understand, and fixing several bugs in the process (one was even by accident, we'd made note of it, then later when we went to fix it, it was already fixed).

[cj]

> Or, it could be like asbestos

If it is, the fall out will be way worse than if AI ends up living up to (reasonable) expectations.

If it doesn’t, we are going to see over a trillion dollars of capital leave the tech sector, which I think will have worse impacts on the livelihood of tech workers than if AI ends up panning out.

This is something the naysayers need to grapple with. We’ve crossed a line where this tech needs to work simply because of the amount of money depending on that fact.

[lelanthran]

> If it doesn’t, we are going to see over a trillion dollars of capital leave the tech sector, which I think will have worse impacts on the livelihood of tech workers than if AI ends up panning out.

I don't think it will be worse; if AI pans out the world would be able to continue without a single programmer left. If a trillion dollars leave the tech sector, all those programmers employed outside of the tech sector will still have jobs.

[toraway]

The asbestos hypothetical is a bit different than the "bubble popping" economic crisis scenario though. In this world, AI would just continue being adopted and shoved into every nook and cranny into which it can be made to fit, with valuations only getting bigger and bigger.

The damage would come much later, well beyond the point where it could be simply pulled out and replaced without spending massive amounts of money and would also basically necessitate training an entire new generation of engineers.

Then the AI giants would start appearing vulnerable like cigarette companies in the 90s while an AI Superfund and interstate class action are being planned but Sam Altman would already be a centitrillionaire at that point so it would be someone else's problem.

[wan23]

Have you ever encountered the very common real life situation where there's some software that works, and you have a binary for it but you either don't have the source code or it doesn't compile for whatever reason? This is the pre-LLM world. Now, do you think LLMs make this situation better or worse? You may not know what's wrong with your software or how to fix it, but unlike in the past you can throw compute at trying to figure it out, or replicating a subset of it, or even replicating all of it depending on what it is. I think LLMs are making this situation better not worse.

[lelanthran]

I think the problem with that sort of thought is that the burgeoning sizes of output for even trivial software makes it almost a certainty that:

a) The stuff output by the existing LLMs is too unwieldy even for them to handle , even if the product itself is a glorified chatbot.

b) If all software is throwaway, then the value of all software drops to, effectively, the price of an AI subscription. We'll all be drowning in a market of lemons (https://en.wikipedia.org/wiki/The_Market_for_Lemons), whilst also being producers in said market.

[kingleopold]

another aspect is amount of code LLMs can handle went from few lines to small codebase in few years, so future is just possible for a lot bigger codebases?