[tuesdaynight]

Why there are so many people that still believe that AI coding is a fad? It's something that started less than two years ago and companies are already paying thousands per seat. I know one that gives you 5k per month. Which other tool went from nothing to this level of acceptance so quickly?

[OptionOfT]

Because companies are betting that this spending will allow them to reduce cost by firing people.

Right now the AI LLM PRs we're seeing are just introducing more work for other people, while these so-called builders are looking good with their new dashboards and functionality they're demoing.

But you can't talk to them about the flow of the code. You can't ask them for their thinking as to why certain things are.

It's not built up from the ground with experience from x people taken into account. It's materialized from nothing, with no foundational separation, and barely any abstractions.

No one wants to touch it. The PRs are too large, and the 'authors' of the PRs aren't on call with us.

They get all the glory, but do none of the work.

It's kinda like designing a house and then sending it to an architect and engineer saying: make this work.

[saulpw]

> But you can't talk to them about the flow of the code. You can't ask them for their thinking as to why certain things are.

You can absolutely do this. It's even right most of the time.

[chmod775]

Let's be real. Most of the time you ask an LLM "Why did you do it like this?", it responds with something along the lines of "Oops. My bad. You're right to point this out."

You even have a fair chance of getting a response like that when there isn't anything wrong and the question wasn't rhetorical - which perfectly illustrates the level of the genuine understanding LLMs operate at.

[seventhtiger]

When you criticize AI, always remember that the alternative is the average employee. Today's models are pretty good.

[devin]

A lot of people think they're above average. A lot of them are wrong.

A lot of average people are producing gigantic messes. At least previous to this they were gated by their mediocrity.

[Frieren]

> the alternative is the average employee. Today's models are pretty good.

I have never seen anywhere in the world people that hates so much the working class as people do in the USA.

In my country the average employee is competent, they do their work and create wealth for the nation.

Again, only in the USA people think that billionaires are the ones creating value. Total non-sense indoctrination.

[seventhtiger]

I'm not American or ever worked in the USA. It's not a judgement of human value. It's a judgement of work output.

[gamerslexus]

To adequately validate work you must be at least at the same level, so if you were right (which dunning-kruger suggests unlikely) that would mean your "terrible" average employee is given a tool that will 10x their output which they cannot even check for correctness. And correctness will be low if the average employee is bad like you say, because it means they will give badly specified tasks and even with the best of us it's garbage in, garbage out. I am sure there is no way this can backfire.

[seventhtiger]

All enablers also enable mediocrity. That's not new. At least when the non-mediocre engineer has to work with someone, they can have a tireless responsive partner.

I find this varies by individual, but the AI taking care of so much boilerplate and rote work of coding, and taking the role of architect, test designer, and reviewer is a lot more productive for me. Check the code may take the same skill, but it's an order of magnitude less work.

[cyh555]

and have they totally got rid of the average employees? They can blame the models for the production outages already?

[partyficial]

when you criticize the average employee, always remember that the alternative is the average employee with AI.

[djeastm]

I remember hearing (perhaps last year?) that the model companies have specifically tried to obfuscate the "thinking/reasoning" behind the decisions the models make so as to prevent cheaper models from training on the reasoning logs. So asking one "why did you do it like this" might be not fruitful.

Not sure if that's true or if it might be influencing what you're seeing, but it's a thought.

[NewsaHackO]

I think that has to do more with the thinking "train of thought" that some models show as what the model is processing before making the response. There shouldn't be a distillation risk with actually asking the model to explain why it made a decision and getting the response.

[saulpw]

This has happened to me, so I put this in my global CLAUDE.md, and it seems to help (I don't remember getting the response you mentioned for awhile now):

    **Lead with the answer when asked how/which/whether.** Name the command/mechanism first; a question seeking understanding isn't a go-ahead to execute. Answer, then offer to act.

[dmayle]

That's because of a fundamental misunderstanding of what an LLM is. The only correct answer to "Why did you do it like this?" is that the specific combination of input text and RNG state caused this particular output. There's no reasoning to be had.

* EDIT * What's with the downvoting? That's a correct description of what happened. You can't ask an LLM why it did something and expect a coherent response, because there's no thinking chain, and no stored thinking state... At best, you can get a reconstruction of how the context relates to the output (basically a summarization of the context).

[baggy_trough]

Can't remember the last time that happened.

[javier2]

Happened to me at least three times the past 14 days. I point out where it made a design decision that causes data loss. «Oops my mistake»

[theshackleford]

I encounter it constantly with the latest models. Claude is particularly prone to it.

> I shouldn’t have said that with confidence

> I got ahead of myself there

> I overstepped, allow me to correct that

It’s wild seeing how often it’s wrong, and I only know it’s wrong because I am an SME or actually reading the sources. Most of my coworkers are not SMEs with what they are asking and do not read the sources.

A huge part of my job now is fixing fuck ups and failures resulting from these slop jockeys who have already moved on to slop up the next task.

[therealdrag0]

So what? That doesn’t negate the value they provide.

[datsci_est_2015]

I believe the “them” the OP was talking about was referring to the people opening the PRs, not the LLMs.

[saulpw]

My mistake, that is definitely a different scene.

[ssss11]

And you can certainly tell it the flow you want (and any other constraints) in the prompt.

[HNisCIS]

It's so fucking bad. I'm watching a team try to maintain a huge dashboard/control application that interfaces with a large amount of hardware using solely AI workflows.

Literally nothing works, all the timers/time counters are different across the pages, constantly commands hardware to do stupid shit, breaks during critical moments/in front of clients.

Eventually mgmt had to institute change freezes for high profile events because the team was breaking too much shit all the time.

The average C suite dipshit doesn't realize that the performance drops off a cliff once your project is more than some fraction of the context window so they will make pretty dashboards all day long but once you need to cover all the edge cases of a real system it all explodes.

AI isn't trained on the type of software style we'll need to create systems using AI, it's trained on how we used to write software. It doesn't reuse code or elegantly structure annoying, it just adds more code until the thing builds and passes some fake tests, even if half of it is functionally dead/unused.

[scubbo]

> But you can't talk to them about the flow of the code. You can't ask them for their thinking as to why certain things are.

There are plenty of valid criticisms or warnings about over-reliance on AI coding, but this is not one of them. Today, I am using a semi-autonomous agentic coding system which has an `interview` functionality built in - when it spits out the PR from the input, if you have questions about the motivation or context for a particular choice, you can start up a clone of the original agent in a sandbox to question it.

Now, you might claim that those responses aren't always reliable, accurate, or consistent, and that claim has a little more weight (though, in my experience, decreasingly so) - but it is _certainly_ not the case that you cannot interview an agent about choices made. I'm literally doing it every day.

[OptionOfT]

Sorry, I meant interviewing the PR author for certain choices.

[scuff3d]

Literally in the middle of ripping apart a vibe coded mess at work to figure out what's even worth keeping. Not fun :(

[bvcp]

use ai to do that

[scuff3d]

Can't. It's a worse case scenario. It got vibe coded but I don't have access to AI tools to undo it. Basically the company was running a test on some tools, one engineer went ham and the thing ended up getting used, then the company decided to drop the ban hammer on the tools.

[foolserrandboy]

What happens if you just keep vibe coding is? Does it whack-a-mole fix one area and break another?

[com2kid]

> Because companies are betting that this spending will allow them to reduce cost by firing people.

I've never worked at a company that didn't have a technical backlog measured in years.

[LtWorf]

If they don't hire to get it done it means they don't think it's really important to get it done.

[tuesdaynight]

That is an amazing point that invalidates the backlog in my mind. Stated vs revealed preferences in the end.

[lbrito]

That's just a non sequitur. "companies are already paying thousands per seat" has zero correlation with something being a fad or not. There are much more reasonable rationales explaining why companies are acting the way they are than "because AI coding is not a fad"

[Kiro]

It's just silly to claim it has zero correlation.

[tmp10423288442]

Can you name a service that charged companies thousands/seat/month that turned out to be almost or completely useless? There's lots of random services sold to corporates that are not very useful (all the random benefits besides health care, life insurance, and other big-ticket items), but the per-seat charge of those is much smaller.

[edent]

Google Jam Board (and other digital whiteboards) had high upfront capex and lowish opex. Probably close to the price for how often they were used before being killed off.

Same with the MS surface(?) tables (not tablets). I saw load of companies buy into the hype and then discard.

[marcosdumay]

There are so many. Can I start with Oracle databases?

[therealdrag0]

Oracle DBs have powered enormous numbers of applications and economic value.

[iammrpayments]

Companies love to waste money on that kind of service, before this website became everything about AI, every week someone would post how they saved a gazillion dollars by leaving vercel or AWS to self hosting as an example.

[therealdrag0]

So you think AWS is a fad?

[sdevonoes]

Not a service, but do you remember Scrum Masters? We had them as full time employees not so long ago. Pure fad.

[therealdrag0]

Hah. Great example actually. But far less common than AI afaict.

[ThunderSizzle]

I hope this is sarcasm, or "half" my job doesn't exist or something. Or you talking about full time non-dev scrum masters?

[oblio]

Yes

[mike_hock]

Every consultant ever, but to be fair that's not per seat.

[LtWorf]

Hey I'm a consultant. They pay me to be a regular developer but they cannot hire since they just fired thousands of people which they apparently did need, turns out.

[overfeed]

> Can you name a service that charged companies thousands/seat/month that turned out to be almost or completely useless?

The Concorde turned out to be fad (not "useless" - which was your reframing.) Touted as the future of travel, each seat cost about $20,000 of today's dollars, but it turned out even at those high prices people and companies were willing to pay per-passenger, supersonic trans-Atlantic air travel is not economically viable, and was discontinued.

[ipaddr]

Oracle and some company wide Microsoft licenses.

[therealdrag0]

These are clearly useful.

[LtWorf]

All the NLP experts that companies bring in to make those seminars despite it has been debunked decades ago for example…

[Barrin92]

>Why there are so many people that still believe that AI coding is a fad?

Because there's not a single piece of evidence that this has improved the quality of the delivered software, or for that matter even the speed of features any of these companies produce, in fact if anything the opposite.

The point of software development, the hint is in the name, is to develop software, not consume tokens. If Uber was now full of 10x engineers the stock price of Uber would be up, not down on a yearly basis. Hilariously enough the only company whose stock price is up appears to be Antrophic

[tuesdaynight]

I don't believe that the quality is the best metric for these companies. I doubt that Google has top-notch code quality in every product they developed, but it does not matter if they are making billions per month. Furthermore, I honestly believe that the quality stayed the same, at least.

[sirsinsalot]

How dare you mention evidence! This isn't engineering you know!

[agumonkey]

I would use these exact facts as a sign that it's maybe not what it seems. It's much too big and too fast to feel stable. It might keep at that level, increase even more, or drop down to a saner level of use / allocation.

[teeray]

I can see a corporate future where tokens are haggled over in department budgets just like any other line item. Some projects will get more of them, other projects will get less of them. "Use AI for everything" will become "use AI economically and build things that outlast our budget for it."

[mekael]

Neat fact, those kind of conversations are already happening at ${DAY_JOB}.

[Aurornis]

> It might keep at that level, increase even more, or drop down

Bold prediction. :)

I think anyone predicting a drop or near-term flattening is not thinking beyond the online bubbles where these tools are discussed. In a local tech meetup a lot of the normal companies are barely coming online with AI tools at their company, and even then with very low limits.

[johnfn]

So it might either go up, stay the same, or go down? :)

[agumonkey]

heh yeah, i'm also selling trading advice :p

[toasty228]

There is a whole spectrum between "ai coding is a fad" and "unlimited tokens for every employees we don't even care if it actually ends up being a net positive financially"

[tmp10423288442]

> "unlimited tokens for every employees we don't even care if it actually ends up being a net positive financially"

That was clearly a short-term trend that would obviously get fixed. Doesn't say much about AI coding as a business model.

[tokioyoyo]

“AI coding is a fad” is not just one big camp of similar-minded people. Different groups have to give up on their pre-existing beliefs in order to be ok with AI coding.

Think of people who were very strict with variable names. People who pushed for multiple-levels deep of abstractions for a single API logic that’s not going to be reused. People who believed that coding is craft, rather than just a process to get to the end during work hours. This makes most of these people’s points more-or-less moot.

I was in some of those camps, but I’ve seen coding evolve in the last 15 years. So I understand that these priors need to be updated, as most arguments don’t apply to today’s world.

[fragmede]

What's an int vs a float vs a boolean? What's a function? What's a class? What's a variable? You don't actually need to know the answer to those questions in order to vibe code. That's a lot of priors to update!

[tokioyoyo]

Just to go on record, as of today, I’m a big believer that a person that knows all that stuff is much more productive with AI-coding than a person who doesn’t.

I have no idea how we can get people motivated to learn these through trial-and-error when AI coding exists though. I remember the days of spending hours on stupid bugs that AI can resolve within a minute. But I recall learning heavily from those experiences. Oh well…

[grogenaut]

yes, but a person who doesn't know any of this stuff is infinitely more productive with ai than someone who isn't when it comes to many things.

we've got product folks vibing out prototypes (not shippable but clickable) in our main front end in a few minutes to an hour. This would previously have involved 3 people and several weeks, or a ton of figma and documents to fill in the gaps. This saves weeks to months and lets them really experience the items.

Then they hand it off to someone who knows all that stuff who is also using AI and the impl also gets done faster.

The PMs are either moving infinitely faster, or at least 30x faster and not blocked constantly by others.

basically you're not comparing people who don't know much (tech) with those who do, you're comparing them before and after access to AI.

[scubbo]

I like the presentation I heard from a Principal, that AI tools amplify your competence. If you start out incompetent, it'll just allow you to be incompetent with greater scope and (negative) impact.

[mewpmewp2]

I honestly feel like my own learning has accelerated after using AI. Simply because now it's so easy to write the same thing in so many different languages, I can e.g. learn pros and cons of each language, which otherwise would have been I think unfathomable to me. I have now created so much stuff I wouldn't have had time to create.

I setup k3s, and tons of what would be otherwise unnecessarily complicated stuff on my laptop for my side projects with additional home servers, smart house stuff. Otherwise k8s and things like that would have been daunting to learn and in theory and without constant professional exposure, etc...

Microservices in Go, Rust, which I didn't have any previous experience with, games in C and other languages. Didn't know anything about low level memory management before. Was just mainly TypeScript person. Just constantly building random fun stuff.

[tokioyoyo]

The question is if you already had intuitive understanding of what those things “are”. The languages and systems have been easier to learn once you picked up a couple. Same applies here as well.

The question is, how quickly does a junior with no experience builds intuition without trial and error.

[mewpmewp2]

But surely, it's a matter of curiousity? If you are curious you will naturally want to look deeper to understand what is going on. If you are not curious, then you wouldn't have done very well before either.

[harry8]

When I started I learnt something about coding from VBA macros to automate excel.

Often that started with the macro recorder. Then you worked out what that "recorded" code/sludge did, removed the crud you didn't need or want, improved the logic and so on. I bought books to understand it better. Now you can ask a (different) LLM "what is this? why is it used? How would I?" etc which is probably a faster learning curve than books, newsgroups and old school personal home pages with good info.

I would have been quite surprised when I first used a VBA macro in anger just how far I would go down the rabbit hole. C, asm, verilog, Linux were no part of what I originally signed up for!

Some people will specialise in the equivalent of recording macros and go no further. And this will be fine for code that gets it done but doesn't matter too much in the other dimensions (security, reliability, usefulness without the authors' support, etc.) Much like VBA utilities inside companies that were useful way back when. Other people will want what they produce to be better, even good, and they will learn about floating point [1] and all the rest, much as I did. Probably learn pretty fast too. [2]

[1] https://docs.oracle.com/cd/E19957-01/806-3568/ncg_goldberg.h...

[2] Working out how to write an excel vba webserver and using it to collect and and collate summary data from various divisions into reports was seedy as hell, solved the actual business problem (given ridiculous but intractable constraints) and isn't something you can record. We all have stories from a misspent youth that we're simultaneously ashamed and yet somehow proud of.

[nomel]

And, you don't have to vibe code. A competent developer can make great use of AI. I think a developer that can develop the system themselves is the most accelerated user.

[malfist]

> You don't actually need to know the answer to those questions in order to vibe code

No, but you do need to know the answer to respond to that 3AM page about prod being down.

[devin]

"as most arguments don't apply to today's world" makes me want to roll my eyes so hard at you. The vast majority of problems we had with building complicated systems are all still just sitting there. People are speedrunning relearning things we've known about software engineering for decades.

The more things change, the more they stay the same.

[rootusrootus]

Between AI and the stock market (which of course relates directly to AI), I’ve lost count of the number of times I’ve heard lately another variation of “this time is different.” Sometimes so close to those words that I wonder why the person speaking them doesn’t feel a bit tingly. Great big warning signs all around.

[tokioyoyo]

The examples I gave, and the arguments that usually support them don’t really translate into “building complicated systems”. I was talking about the arguments in support of variable naming flamewars, etc.

I’m not proponent of AI generating everything without any supervision as of now. But willing to change my mind when it gets better.

Most software engineering jobs are not cutting-edge tech, or research, or solving unsolved problems. Integrations, APIs, figma-to-react pipelines, devops and etc. is what people get hired for. All those can be done much faster in the same-or-better quality by an experienced person with the supplement of AI. It’s hard to imagine any company would go against the grain and slow things down on purpose.

[devin]

So I accept that “nonsense arguments are nonsense”, but with some minor differences of opinion. Naming of things matters insofar as you care as a human to actually conceptualize the system you’re building. You can call all of this stuff minutiae, and on some level I kind of agree, except for the general vibe of _caring about the quality of the stuff you produce_. That is something that still matters whether it “works”. Like, yes you can get an LLM to gen some junk, but _is it any good_ is still something you are in charge of.

As far as “boring systems are boring”, I can tell you from experience that I work on a pretty boring system, and AI is not all that meaningful in terms of its impact, and it’s not for a lack of trying.

Can it help me create a migration and add an endpoint and such? Sure. But those aren’t the hard problems. They never were.

It’s funny that you think the idea of slowing down is such a bad one, but it is another well-established truth. Slow is smooth, and smooth is fast. This notion of break/fixing your way to prosperity by way of 10,000 ill-conceived PRs is a fool’s game.

[tokioyoyo]

I'm sorry, you might be right. But this simply doesn't reflect my daily reality. All I can say is, nobody in my org is creating 10,000 PRs. But everyone is using Claude Code for virtually all commits. We've been doing it since about Opus 4.5ish. So far, so good.

Generally we've modified our timelines heavily, systems are working as intended, company is still making money. There are some AI-authored commits that had mistakes that we didn't catch, but I'm sure this could've been an issue even if all were human-authored. I know first-hand multiple other companies who are doing exactly the same thing.

I agree with "slow is smooth, and smooth is fast" for mission critical systems. But super majority of systems are, indeed, not mission critical.

[devin]

I think we're probably talking past one another a little bit. I use LLMs. Daily, even. I've been doing so since around the same time. The vast majority of people in my organization are doing the same.

I have watched some projects absolutely explode in LOC added, number of PRs, etc. but I think the more interesting question is: how much of it is directly being done to add customer value, how much of it is churn, etc. you might get some interesting answers.

As so frequently seems to be the case for you and I, we kind of agree but then you drop something that just does not compute for me: "slow is smooth, and smooth is fast" is not specific to "mission critical" systems, it is generally applicable.

As I said in a previous comment, I work on a fairly boring system. Its "criticality" is debatable, but in general we make the same kinds of boring guarantees to our users that even mediocre SaaS products offer: a few 9s of uptime, zero-downtime deploys, etc. AI has made aspects of working on this system easier, but in terms of API surface, how users are using it, how to safely advance its state without breaking existing callers, data migrations across services, and so on, very little has changed.

[therealdrag0]

I have the same experience. Slow is smooth with AI is still productivity improvement.

[sirsinsalot]

Fear of loss to competitors embracing a technology creates a fear driven adoption.

Let me ask you this: is any technology worth so much break-neck adoption without first seeing clear evidence of ROI? No. The adoption is irrational.

[anamexis]

What makes you think there is no clear evidence of ROI?

[techblueberry]

All of the articles and CFO’s saying so, and companies like Uber cutting back on AI spend.

[simonw]

Uber cutting back to ~$1,500/engineer/tool/month makes it look to me like they think there's at least $1,500 of monthly ROI to be had per engineer.

[NichoPaolucci]

1500/Mo per engineer is such a small price considering the base salary of these employees, Maybe Uber knows something we don't (the 5X engineering ROI isn't there for them?).

Judging the ROI of an engineer is hard. Adding AI on top of that makes things worse, I think. I've heard AI makes engineers 3X, 5X, 10X and even 100X.

If I told my CEO that I was 4X more effective with AI, I am doubtful he would be willing to spend even 1X my salary on tokens. Even though he would be making out in the end.

At some point the ROI is pretty much vibes, man.

[techblueberry]

So touche, but since it's usage per task it's kind of weird.

This means that the average engineer is efficient at (say) identifying the first 10 tasks they should do but there are diminishing returns after that? That seems like a weird pattern. Wouldn't it be more likely that certain tasks have a ROI based on how efficient the task is generated?

Like I'm trying to imagine in my head, if you think an engineer is more efficient with the tool, why deny them more tokens. I guess so they think to use them more efficiently?

So, maybe I conclude that I think your conclusion that there must be $1500 per engineer is flawed. And even if it were true, I don't think the benefit would be evenly distributed. I suspect this is a first pass at figuring how to budget them and there will be a second pass.

While it certainly reeks of motivated reasoning, Jensen Huang assertion that an expensive engineer should be using at least their salary in tokens feels more logically sound to me (assuming the average engineer is efficient at using tokens, I have a feeling it's a normal distribution)

[therealdrag0]

Setting a cap motivates developers to invest their tokens wisely such as choosing the right models and not burning tokens for fun or side projects, same as any budget.. it’s not any deeper than that.

At my company we can ask for temporary cap limits if it’s justified, which is fairly common.

[simonw]

"I suspect this is a first pass at figuring how to budget them and there will be a second pass."

Completely agree with that.

[javier2]

Because the vibe coded stuff is sometimes great, sometimes it breaks stuff, sometimes it breaks things that we fixed multiple times earlier. The PRs are too large, nobody can review that mess and you better be on call for your deployment. Maybe it will get better, maybe not. I dont know yet.

[Gigachad]

The massive PRs is something that probably has to end. You can ai generate smaller changes in reviewable PR sizes. It probably even helps the AI code review tools to break the work in to smaller logical chunks too.

[javier2]

Yes you can, and this is still the most realistic use of AI llms, but this is a 2x multiplier, not 10x or 20x

[therealdrag0]

What about that means AI coding is a fad?

[marcosdumay]

Oh, it won't get any better. LLMs already trained on every bit of code ever published, they won't get any more material.

[therealdrag0]

They can be reinforced with best practices and context windows etc will increase.

[throwatdem12311]

If anything the snake is eating it’s own tail because now it’s training on vast amounts of its new slop…dragging down the average bar of quality.

[anthonypasq]

perhaps the personal computer? Companies were spending 3-5k (10-15k inflation adjusted) on every employee for just hardware.

everyone making comparisons to the dotcom bubble seems misguided. this is clearly computing 2.0 imo

[thewebguyd]

No disagreement on computing 2.0, but companies spending 3-5k per employee for hardware isn't generally a monthly cost. It's a at the time of hire, and then once every 3 to 5 years after that, for a monthly amortized cost of about $50/employee.

I have my concerns with current inference pricing in that there's a non-zero possibility for a rug pull in the future for the subscription plans for organizations and individuals that can still use them. For now, its only companies larger than ~150 users that need to pay per token, but what if that wasn't the case? Not every company can afford over $1k/month/employee to give them access to AI tooling, further making it harder to compete against the behemoths. If we get to a point where an individual can no longer pay $100/month for nearly unlimited usage and instead must pay per token, that's going to be a problem.

Personal computing eventually became an equalizer (until we started centralizing on mainframes again, aka the cloud) because it got cheap. My hope is that inference also gets just as, if not cheaper.

I have high hopes for local AI and open weight models and we will continue the ethos of local, personal computing and not needing to offload everything to OpenAI/Anthropic/Google, etc. to get work done once the hardware and hardware availability catch up.

[GrinningFool]

Any kind of rug-pull is a serious concern. Companies are re-orienting their entire development processes around these tools. Sure they can go back, but it will require a much larger and more expensive effort than to transition in the first place.

All companies who make this transition will be more or less at the mercy of model providers.

[dghlsakjg]

Every employee doesn't need $1k in token spend per month, either. That kind of spend makes sense for technical workers in r+d.

Most other workers are served fine by $20-30 worth of tokens on a budget model. You don't need Opus to help support write emails.

[tmp10423288442]

No, but you do want Opus-tier models to do desktop and office software automation (think about people who intensely use Excel and the like). Actually those might take even more tokens that coding in a lot of cases. Why do you think Claude Cowork is successful, and why do you think Codex is leaning so hard into Computer use?

[dghlsakjg]

I wonder if you will see app makers begin to open APIs (MCPs) up in ways that replace computer use. Computer use via human interfaces is pretty hacky IME, and if you can use an app that exposes spreadsheets in a way that reduces token costs by 90%.

I'm optimistic that the demand for AI accessibility will drive programmatic interfaces in places where companies were previously reluctant to.

[dghlsakjg]

The Dotcom bubble is an interesting comparison.

The general thrust that everything would be online was correct, it was just that the market mistimed and misallocated of capital by a decade or more. There was massive spending on infrastructure capacity that we wouldn't end up needing until the 2010s. There were hype driven valuations completely disconnected from business fundamentals just because a company was an 'internet' company. Things were going from cutting edge to obsolete in less than a year. There were breathless promises that this was business 2.0! Of course, none of that sounds remotely like what is going on today...

I'm optimistic about AI, but I also don't think that it is going to change everything as fast as promised.

[threetonesun]

The question you always have to ask is what problems does it directly solve. I personally think most of the current problems in software development and really the world at large are not time-bound problems but alignment issues, and all an LLM can really do there is be some 3rd party oracle that gives you an answer without needing other humans to agree with you.

[squidbeak]

> The question you always have to ask is what problems does it directly solve

Most directly, human labour. Labour is always a problem for capital. At a certain level of AI competence, businesses don't need to pay humans to complete the work they need doing in order to operate. I don't think anyone would dispute AI competence isn't growing steadily.

[rafterydj]

I agree with you. I think that if we're talking about actual reliable problem solving, we have to be discussing robotic / drone systems. Software is as complex as you want to make it, and always has been.

[jghn]

Two things can be true at the same time. It can be true that this is here to stay. It can also be true that companies are grossly overvalued right now and that the market is irrationally exuberant. This would mean we could both have a crash and also see AI coding be the new future.

[pixelesque]

Hardware's not generally a subscription, monthly cost though.

You update it for them every 3/4 years (if they're lucky).

It probably makes a bit more sense to compare it to existing software subscriptions like Office, or the old-school 'per-seat' licenses per user for software.

[thewebguyd]

There's some software that can cost $1k or more per seat/month, but it's pretty rare. Big tier ERPs usually fall in the ~$600/seat/moth range, specialty engineering stuff can hit over $1k, Bloomberg terminal, etc. I wonder if what Uber's building with that $1.5k/month/employee is actually delivering the same value that something like an ERP would to the entire org...

[pmg101]

I think the right comparison is the invention of the microprocessor. At that time people were grappling with a lot of the same things we are today - would it automate jobs away, would it transform education and the work place, etc.

[maplethorpe]

> Which other tool went from nothing to this level of acceptance so quickly?

NFTs? My company had nothing to do with blockchain but I ended up working on NFT integration regardless.

[tikhonj]

I still believe Scrum is a fad and yet companies have been spending obscene amounts on to push it down developers' throats for decades now.

[therealdrag0]

Scrum spending is very rare IMO. No company I have worked at pays anything for scrum.

[perlgeek]

As a side note, I wonder when we'll hear the first reports about employees reselling (parts of) their token budget.

Probably not worth it risking your job for a 200$/month good, but at 5K, I'm sure some folks will be tempted. Especially if companies do stupid things like token usage leaderboards.

[themafia]

Why are there so many people who mistake simple anecdotes for actionable data? Why do the majority of businesses fail rather than succeed?

[LAC-Tech]

Because we have spent a lot of time and money using AI to generate code and have been unimpressed with the results.

As for why they got accepted so quickly 1) the industry's long running desperation to deskill computer programming 2) the addictive psychology baked into LLMs "That's an elegant solution! Shall I ... ?"

[asadotzler]

Also, a bucket for VC to put all that NFT, IoT, blockchain, VR investment into. VCs gonna VC and the last 15 years of bets failed so the last few years have been a transition away from those toward "the next thing".

[jbvlkt]

Because writing huge amounts of code is easy for humans too. Agents already proved that they can do it. But are agents able to maintain it? I do not know and unless I know for sure, I am not fully committing to AI generated code.

i.e. I am able to write about 1k lines of code of "acceptable" quality per week. Which means in 1 year, there will be about 5Ok LoC. I am pretty sure, that I would have to spent like 60-80% of time to maintain 1st year code and the rest to make new features in the second year so I would have to hire more people and spent time to onboard them to maintain velocity. All of that are rough estimates, probably overoptimistic and way worse in 3rd year. Good luck doing such estimates with code agents. Even worse if you already have huge amounts of legacy code.

[jujube3]

It's cope. People desperately want to believe that AI coding is going away so that they can go back to partying like it's 2020.

So there's a huge number of HN posters claiming that the price of tokens will go UP over time rather than down (that's how Moore's Law works, right???) or that code bases that AI contributes to will spontaneously combust, or something.

[Der_Einzige]

Token costs do go down over time for sure due to software optimizations (i.e. better attention kernals) but acting like hardware INFLATION isn't happening for at least a few more years is just nonsense. Objectively an A100 is more expensive to rent today than it was in 2024 (a 7 year old GPU - Big short guy is a turbo idiot) and rising. As such, over short time horizons, it's possible to see limited amounts of "price per token goes up" for the same model.

[oblio]

It's a mix. If the current wave of LLM businesses crater, demand for LLM specific hardware (and related hardware) will crater. GPUs were propped up by crypto currencies and now by LLMs. They're still great at doing fundamental math operations, but for their value to stay up another massive business opportunity involving matrix multiplication and the like would need to rise as soon as the current business cycle winds down.

Not impossible, not unlikely, probably 50-50.

[dofm]

I don't think it is unreasonable to say both will happen, is it?

In the long term, tokens will fall in price. Obviously. (If "tokens" continues to be the unit)

In the short to medium term, for the IPOs to succeed, people have to start actually paying for what they are using, so the price will go up, and is going up, quite a lot. Once their value is set they will slowly fall from that point (or some point maybe halfway, depending on how much the market is willing to continue to subsidise).

I am an AI cynic, but I am now an informed cynic; I am learning agentic tools so I know where they are useful and I know my enemy.

I think the "fad" here is cloud-based, metered AI being a dominant work mode.

Nothing, so far, has suggested to me that any other outcome is likely than edge- to local-scale, on-device, on-laptop, on-prem models getting good enough to the point where people use them by default and use the cloud models only when they need the extra oomph.

I cannot believe that there is anything other than an enormous incentive for companies like Uber to find local, small model and on-premises solutions to their problems, not least while pricing is so changeable and people are getting nasty surprises.

Betting on OpenAI and Anthropic being around over the long term in the form that they are now, that feels like valley hopium. Utility monopolies essentially always derive from physical/geograpical limitations, don't they?

[jujube3]

I mean, there's an "enormous incentive" for people to run their own data centers rather than using AWS. And yet, cloud is growing and on-premise is shrinking.

While I hope local AI continues to exist, I'm skeptical that it will take over, for the same reason running your own servers hasn't taken over. It's just hard, and involves spending huge sums of money up front.

It's also not really clear how much tokens are being subsidized. The discussion reminds me of Uber. For years people on HN claimed that Uber was going to collapse once they ran out of VC money. Then... that never happened, and everyone just moved on to discussing other things.

[oblio]

Infrastructure is massively complex and multi cloud is super hard to do. Switching LLMs is... a drop down.

Now, that doesn't mean running your own LLM will be easy, but this will mean it's a lot more likely that there will be at least regional LLMs, in my opinion. I.e. there will be Google, whichever (if any) is left standing of OpenAI or Anthropic, and then there will be Chinese hosted LLMs, probably Indian hosted LLMs, European hosted LLMs, plus LLMs hosted on managed services (i.e. Bedrock). For sure I see large banks on the like being able to host the best OSS or even licensed LLMs on their own cloud infrastructure accounts (i.e. at AWS, Azure, etc).

And that's on top of the LLMs running on owned server infrastructure plus actual local, on device LLMs.

[jujube3]

You're using the future tense, but all of those things already exist. Google exists, Amazon Bedrock exists, DeepSeek's cloud product exists, etc. etc. But this isn't relevant to what the post you are replying to said, which is that "cloud-based, metered AI being a dominant work mode [is a] fad". Since all of those things are cloud-based, metered AI.

[dofm]

I was talking more about on-premises, on private cloud and on-device stuff, as I said.

If you look at what Uber is spending per developer per month, they clearly have some headroom to consider whether more-local, unmetered AI tools on device, on premises, in private cloud, can be cost-effectively used to cut down how much money they are pouring into Anthropic and OpenAI. Not least because a bit of centralised effort might lead them to distilled models that are better for their purposes. Some of that budget could go into simply putting a bit more capacity on a developer's desk.

Can they do it now for everything? Obviously not. But IMO there is no reason at all for planning and scaffolding tasks to be done with cloud models, and there are many reasons why it might be better to do document processing without leaving the premises.

The incentives are there on the technical, operations and particularly on the business levels, and the relative disruption of the switch really small, considering that all the tooling can use different models for different tasks already. They must at least be investigating the possibility; it's irresponsible not to.

[maplethorpe]

> So there's a huge number of HN posters claiming that the price of tokens will go UP over time rather than down (that's how Moore's Law works, right???)

I mean, Github Copilot's pricing just went up considerably, so I guess they were right?