Thomas Midgley, Jr. must have been a fascinating person. It's too bad rather than being known as president of the American Chemical Society he'll forever be remembered for both leaded gasoline and R12 refrigerant.
Enthusiasts generally don't see a "return on investment" on their luxury cars or their boats either, but they enjoy what they're able to do with them and aren't exactly embarassed about the class signaling of being a high spender.
Add to that the smattering people with genuinely justifiable use cases, and you have more than enough demand for a limit-pushing, highest-margin model of your product platform.
If a new premiere high-margin product sells out "within a month" that means there's a disruption in sales and an opportunity for competitors to meet the demand they just generated while manufacturing/distribution tries to catch up.
It would absolutely represent either a mis-estimation of demand or compromise to some supply/manufacturing bottleneck that they couldn't overcome without sending their release calendar into chaos.
I think I agree with the economic sentiment in general but who is the competitor that can even make something comparable? And by that I mean: Matches the memory amount, the memory bandwidth, the form factor, the power draw, the compute and the OS
In it's role as a local AI engine (for inference, training, or fine-tuning) you don't need to compete on all those factors to be a viable competitor if this were sold out.
Those are hard-to-beat features for typical Apple users, for sure, but this is aiming for a different niche and the potential buyers in that niche may not be as concerned with form factor or power draw (for instance), and some may even see the OS as a negative factor. Those are just factors that happen to come along for the ride since it happens to be an Apple product.
There's truth to what you're saying, but for some perspective: catalogers identify about 400 games published for the 2600 over its entire lifespan; Steam has about that many new releases every week.
That difference in volume, which improvements in AI workflow will keep accelerating, really does point towards personal curation being far more overwhelming than it had been.
With the 2600, you and your friends would probably have a ready working memory of pretty much most of the good stuff, most of the awful stuff, and some insight into the publishers and presentation/packaging cues that point one way or another for an unfamiliar title.
With Steam, if you want to be able to find very personal idiosyncratic gems, instead of just following social media buzz or AAA PR -- one of the most exciting benefits to today's massive catalog -- you have to wade through an increasingly unfathomable amount of slop.
You'll find that design matters when token spend starts facing real accounting.
Tech debt is still tech debt, even if there exist models that can wade through, because it's going to require increasingly sophisticated models navigating increasingly large context windows and increasingly speculative workspace operations to keep making progress on it.
Vendors like Anthropic and OpenAI are laying a pit trap when they demonstrate how their models can independently code their whole platform as it becomes increasingly byzantine and inscrutable because not only do they benefit from internal/prerelease models but they have effectively unlimited spend because all that spending acts as a lure to draw you into their trap.
For everybody else, design still matters. People are just working really hard to make you forget.
Personally I think I could probably be content for the rest of my days running something like Z.ai glm-5.3-flash locally, so I'm not that worried about the token spending (and still can't understand how OAI/Anthropic/etc convinced the market they have any kind of moat to motivate those kind of evaluations, but that's another topic...)
That said, I also feel like betting on readability, maintainablility, taste, etc, being an important aspect of software, at least until code will remain some sort of human readable artifact. We'll still want to be able to understand it and perhaps occasionally add/edit by hand, make sense of it without trusting blindly what any kind of program (LLM based or not) will tell us about it, and so on.
The problem here is not the vendors.
The "problem" is that design mattered when producing code was a truly manual effort. Writing things down, aligning specs, design, contracts, all of that would mold what could come next.
Now ANY design from amazing to terrible can be regenerated and generated dozens of times over for literal single digit dollars.
Cost of tokens is NOT a problem unless you have a codebase with hundreds of person-years of effort. Not many people do.
Honestly, I keep hearing this argument, but the past 2 years have shown the opposite. OAI/Ant are not the only companies providing inference.
There are legitimate FAANG-like companies that have general guidelines about “when to use Fable/GLM/DS” and etc. to keep the costs down. And I think it’ll continue that way.
You didn't address the argument about tech debt. How do you get the greatest quantity of maintainable, high quality code within a given token budget? The answer, at least so far, seems to be human experts in the loop. We've also been hearing for years that LLMs are going to automate away software development entirely, but software job postings are steadily rising.
>How do you get the greatest quantity of maintainable, high quality code within a given token budget?
Doesn't matter as much. The cost of "maintenance" is going down, from what I can see internally, from other companies, and every story i'm reading from other organizations as well. Token budgets are changing, but model quality and effectiveness are going up as well.
> We've also been hearing for years that LLMs are going to automate away software development entirely, but software job postings are steadily rising.
I think this has been contested from day 1. SE jobs might be automated, but jobs might increase, if there's possibility of starting new companies / new investments / etc.
I'm still not clear on what you're really saying. If a human programmer's input doesn't matter at all, then anyone should be able to prompt a model until it spits out the software they want. That might work today for building fun tech demos, but I don't see it happening on projects that have a minimum bar for security/reliability and long-term maintenance. Would you say, for example, a team of 10 managers with no software experience can be as successful as a team of 10 expert programmers at building a large project like an operating system, with both teams having access to the same AI models and budget?
No, because expert programmers will not know what they’re building, and skew the prompts and ask for the right things.
The analogy would be math people with AI vs. non-math people with AI trying to solve some problems. I cannot solve the problems because I have no idea how to prompt it to go specific way. But it doesn’t matter how dirty your scratchpad was, because you got to the solution.
> I don't see it happening on projects that have a minimum bar for security/reliability and long-term maintenance
I don’t get this, because this is currently, right now, at this second, happening across huge projects. My point was that maintainability is less of an issue than before. Also, frankly, over years, I’ve seen bad code that AI wouldn’t even write. So there can be a case that the maintainability/code quality isn’t even going down as the models get better.
Some people just can't turn off their brains and play drone for dozens of hours a week for decades. It feels existentially, aesthetically, and sometimes ethically crushing to spend a whole life doing work you can't expect yourself to respect or value, no matter how much you get paid or how little the work overtly demands of you.
Often, the lack of meaningfully challenging demands being put on you is punishing on its own. It can feel like a relief for a week or month or year, but if you catch a glimpse of that being your whole future, you can come to recognize yourself as being in a mind-eroding secular purgatory.
This anguish is especially common among on highly capable people, high achievers, and those used to some kind of ambition. And by accident of its history, there's a lot of those people in this industry and some of them are going nuts now.
Man, I have the same feeling.
A long time in your life you build the career and now it’s just feeling so empty, like you are not a engineer anymore, now everyone can use AI and without checking code they would have good results.
> now everyone can use AI and without checking code they would have good results
?!!?
No way. Are you sure? What kind of work? Here there’s still a lot of care needed to navigate the LLM work, like knowing when to make it quit, rewrite, refactor, follow your outline.
It feels magic but when I watch people who don’t know what they are doing trying to make something new (not almost a clone of an existing product), they get pretty frustrated.
I once lost out on 3 months severance and a laptop when I quit a place and they shuttered two and a half weeks later. There had been no direction from the top for over a month other than "ehh, do something useful". I was working remotely and slowly going crazy.
> This anguish is especially common among on highly capable people, high achievers, and those used to some kind of ambition. And by accident of its history, there's a lot of those people in this industry and some of them are going nuts now.
I went nuts for years, until I sold off my interest in my dream partnership.
10 years of heaven. All the benefits and none of the downsides of my internal colleagues. Then 14 years of bureaucracy aimed at predictability over progress, which was infinitely more difficult for me to dodge as an external player.
Compensation for my interest was very objectively valued, with the rate of stalled progress priced in. Which made complete sense, while also being its own madness.
I walked away from so much value, but I don't regret it for a minute.
This exact mentality is extremely toxic and is why the historical "anti-work" movements (i.e. Anarchists) have been kneecapped, often by their supposed best friends (i.e. Commies). The major disagreement circa the 2nd internationale was "is work good, but bad that you're exploited and not paid well?" (the Marxist view) vs "Work fucking sucks and we should abolish it" (The Anarchist view)
I can't believe how much mental justification needs to be made by otherwise highly intelligent people (Bertrand Russel wrote In Praise of Idleness) to defend the right to not work.
No, I fully reject any notion of life value coming from work, and those who hold your view are basically jailors to those who don't want our identity defined by work.
That's not how the world works, and I don't need this in a thread where I'm dealing with the grief of a good career. Please shove off.
I would gladly not work and learn cello and physics independently if that were a real possibility, but it's not, and it won't be within my lifetime.
I had a job in a system that required jobs to survive that genuinely didn't bother me. I actually quite enjoyed it most of the time. Now it's permanently dead and I need something else, or I am homeless and starve to death.
> No, I fully reject any notion of life value coming from work, and those who hold your view are basically jailors to those who don't want our identity defined by work.
Most people in the industry right now, even at FAANG and even among people carrying "senior" titles at these places, have little experience with "software design principles" -- tens of thousands of brilliant Ivy League graduates with surreal compensation packages have spent the last decade pulling tickets off JIRA and pasting least-change-possible patches onto existing code for about 10 hours a week while spending the other 30+ hours barely engaged at meetings.
This is maddening. I've been pulling 40/50/60 hour weeks for 21 years in the tech industry at various different companies. I haven't broken 200k base salary, though benefits are pretty great where I'm at. To think I could've memorized some leet code problems, got a job at FAANG and been making 300k base for the past 5+ years while working 10-hour weeks is - yep, maddening.
The best time to be aware of the socioeconomic class differences in tech was 20 years ago, the second best time is now. Also some folks just find it difficult to study leetcode problems purely to "prove" themselves, for various psychological reasons. If you can, it helps a lot, as does graduating from top universities with a direct pipeline into these companies. Social signalling is much more valuable nowadays than capabilities.
Sometimes the grass really is greener - company culture can be actually incredibly toxic and compensation very below market, but when surrounded by people who normalize it most folks will project that experience out to the rest.
Did you go to Stanford or a similar pedigreed college? Unless you did that or broke that 200k barrier already by getting high up in a lower tier company, just memorizing some leet code problems wasn’t going to get you into a FAANG.
They care a lot about prestige. Or at least did before AI. Don’t know what their current hiring practices look like.
Don't feel bad. It is not about skill in those job, it is about "cultural fit". You must project a personality that will fit in with FAANG culture or you won't get the job unless you're famous globally due to having starting some huge open source project.
Comfort yourself with the fact that you did not have to sell your soul, sit through endless woke sexual harassment videos where you are taught that the white man is the source of all evil, and in endless management meetings.
Why are you upset its this way elsewhere? Those kind of working conditions are much more favorable don't you think? Why would you want to work 60 hour weeks?
I think we passed the inflection point of the normal 150-500 Lear code problems, understand DSA and systems design really well. Personally, I think companies are much more selective now and have all reduced the size of their engineering orgs.
There’s always been a percentage of luck getting offers from big tech companies, but it’s way more luck than than merit it has ever been.
The majority of those who get in are able to socially signal, through affiliations with other high paying companies or paper from prestigious (read: socially exclusive) institutions.
This hurt to read but checks out in my experience. These types also tend to love tossing debt over silo'd walls and pointing the finger a lot if/when anything goes wrong.
I'm old enough now to be a protected class, so I don't want people accusing me of ageism, because that's not where this is coming from - but there's a type of person that clearly is on their last job of their career and knows it and I try to avoid them like the plague, I've seen it too many times.
Good philosophy. Don’t write code to show your own cleverness. Write code for the poor bastard who will eventually have to debug it at 2am while that outage timer ticks on and everyone keeps asking how much longer.
The code isn’t for you. It’s for them.
Of course, there’s also a chance you’ll be them. :)
The incentive structures are all fucked up. It's far more profitable for all parties involved to just slop out some barely maintainable bullshit that only just meets the product manager's criteria for external quality while completely neglecting the internal quality of the software [0].
By the time the system starts to experience strain under the weight of its technical debt two years later, the original tech lead/architect of the project has already added it to his resume as another bullet point, found a new job at 20% higher comp, and no longer has to ever look at that code, ever again.
Now it's the next asshole's problem. Good luck!
[0] Freeman & Pryce 2009 for the "internal quality" vs. "external quality" dichotomy
I think part of the problem is the original product manager has also added this as a bullet point on their resume and gotten promoted. They get to watch the dumpster fire from a safe distance.
The 30+ hours were often just goofing off/video games/porn, very few are in 30 hours of meetings. The amount of grift, non-work, fake work, etc that remote well paid tech workers get to do is absurd.
There are hundreds of benchmarks (all noisy), dozens of model families, and dozens of modes and variants within each. Announcements are crafted by publicity teams and involve cherry picking a chart that looks compelling.
As a prospective user, none of of the benchmarks details will matter to you, but the family of models and settings they peg themselves against can give you a hint of where you might want to evaluate them within your own workflows.
As an enthusiast or lay researcher, the more interesting thing is to look at their techniques and any innovations they're exploring in training, inference, etc. Those are usually going to be details tucked below the fold and won't be summarized in a benchmark chart.
As anybody else, why do you even care about this in the first place?
This doesn't just apply to AI. You should know better than to take marketing announcements at face value, nor trust that most "influencers" or "journalists" or "commenter" repeating and discussing those announcements are doing a lot of work as they buzz over what's said.
Don't be a victim to PR spin, but also don't discount potentially interesting work just because it got channeled through a marketing team. Just look for the information you need amidst the noise or move on if there's none there.
In the optimistic case you describe, what smart customers want to watch out for is being lured into vibing your projects into such byzantine slop-complexity that subscription plans and trailing models are no longer sufficient to make progress on them.
Vibe-coders talk about surrendering understanding to the models, trusting that there will always be a model able to overcome and work through any technical debt they happen to accumulate, but the danger that still lurks there (at least for the naive) is that you'll need increasingly large contexts, increasingly sophisticated models, and increasingly large token spends just to keep that ball rolling.
Between profitable enterprise accounts being ineligible for subscription, eager but busy people paying for underutilized subscriptions, and naive vibe-coders falling into their pit trap, you can indeed imagine subsidized subscription accounts being available for a long time and remaining an effective value hack for people careful enough not to fall into the pit trap. But only insofar as they are that careful.
Ethical questions like this are a lot easier to discuss if you take for granted that people are acting in good faith.
If you truly cared that much about Amazon and truly felt library participation was so heinous that it ought be obstructed, I think a lot of people would be very skeptical and a lot of people would disagree with that perspective, but yes, those of us who believed you were acting earnestly would indeed appreciate you standing up for your principles in a way that was impactful but not violent.
There's less skepticism of sincerity here and more agreement with the fundamental concern here, but the respect for principle and action covers both, yes.
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