I feel like there's a bit of AI psychosis in this particular post.
>"These are tools which burn vastly more tokens, but are also quickly becoming daily drivers for the work carried out by extremely well-compensated professionals."
>"Somehow this fragment turned into headlines like Uber’s COO says it’s getting harder to justify the money spent on AI tokenmaxxing, because the market for stories about AI failures remains enormous."
Yes, it's just the yearning for AI failures. It couldn't possibly be runaway costs, record revenues, and massive layoffs. It couldn't possibly be that these tools are lighting dollars on fire by people already paid significantly well and not producing any increase in "value" for it (I recognize that output is 100x but outcomes are flat by all measures).
Being pedantic, but I don't want to lose the meaning of the term: "AI psychosis" doesn't refer to someone who thinks AI is really good. It refers to someone who develops symptoms of psychosis from talking to an LLM, e.g. believing they have developed a new Grand Unified Theory of physics.
I don't know, "workaday professionals will find $200/month a particularly good deal, such that there will be widespread adoption" sounds either credulous enough to support the diagnosis or dishonest enough to dismiss. I am a "knowledge worker" who is doin' fine, has a lot of templated written work/report writing, and there is no way in hell I am justifying that kind of spending to my boss or my family.
"I firmly believe this technology will create business value" is so obviously and categorically different from "Humanity has birthed a silicon god that I have also developed romantic feelings for" that I'm not sure if your comment is even trying to be in good faith
What sort of bad faith would even apply here? idgaf if poster x or y has psychosis or not. "$200 a month is classic addict behavior" seems pretty spot-on to me though, I just don't want to have to pay it, too.
You can't justify $200/month in spending to your boss? Many people charge more than that per single billable hour. I would put your salary side by side with that number, which is your boss's perspective, and reconsider.
Fully loaded costs for an average employee at a bigco are scary. Not $200 but significantly higher than the number on your W2 by the time the company pays vacation, benefits, unemployment insurance, etc.
I've seen people try to argue for resources using reasonable but abstract arguments, and it just never works. The fact of the matter is that I want $200/month, on top of my other asks, and that comes out of somebody's budget. I just don't see folks snapping their fingers and $200 a month (discounted for now!) appears. Good for the other guy I was replying to if that's the case! I just don't see it though.
I think is the classic dilemma where people don’t know how to value their time.
Typical tech worker costs a company around $100/hour minimum. That $200 subscription cost can look mighty attractive if it saves some time or mental load.
I don’t think there is anything about addiction or spooky with that math. I suspect a lot of this is coming from tokenmaxxing firms but on the flip side on our small team, we end up spending about $200 per person per month for tokens using tools like Cursor. We feel the spend is justified with measurable value.
I just cannot imagine zero net productivity gain from AI usage by a somehow experienced developer. Even if it’s happening right now it’s matter of time for people to figure out how to utilize it right. Only exception would be if people are getting the same output but working less, which is still a net positive (just not in terms of output).
Sometimes it feels like theres this opposite AI psychosis, where anything AI is bad and boils the ocean, takes our jobs and makes RAM expensive. Its a component in the current economy, but things like tariffs, closing the strait of hormuz etc is equally bad for the economy. Anyway, just find it strange to be so militantly anti a certain tech.
It's more the tech leaders than the internet. Sam Altman, Jeff Bezos, Eric Schmidt and such get up on stage or interview regularly with a shit eating grin telling us all about how they are coming for our jobs, will make us obsolete, and there is nothing you can do about it.
It's a natural response for society to despise these people who have such contempt for us. It's almost embarrassing these days being at a social function and telling people I work in software, it's got a negative stigma almost like working in gambling or the military.
I think it's a matter of perception because I didn't interpret any of them as being gleeful about it. If you think about it, "AI will take your jobs and maybe destroy the world" is horrible, horrible marketing -- like, your comment is a perfect illustration of how it is received everywhere -- and yet these CEBros can't stop saying it, which indicates to me that they actually believe it.
Oh, now that their IPOs are nigh they're changing their tunes (https://archive.md/s9EO3) but to me that looks more like they've decided to let $$$ prospects override what they really think.
The general public is not their customer base, they don't have nearly enough money to spend on AI. Going to the media and saying "this product can automate so many jobs" is marketing to other businesses who want to use it to cut their workers out.
There was crazy clip of Eric from Google telling a crowd of university students that in the future AI will do everything, and after the whole audience boos him he keeps pushing the point that they better accept it and get on board. The mentality these guys have is sickening. They have no humility and no humanity.
The general public may not be their customer base (except maybe for ChatGPT, which is primarily a consumer app), but it is the voter base. The AI backlash has been brewing for a while and is bubbling over in the form of data-center pushbacks, and talk about regulation has been picking up. Plus, if "AI destroys the world" does happen, even the capitalists looking to further cut out labor will not be too happy about that.
Even if this was not covered in Marketing 101, it was all pretty predictable. Sure, most of these CEBrOs probably have a god complex (probably fueled by Ketamine) but their behavior is also consistent with the premise that they see a job apocalypse coming and they must warn the world about it.
Especially never liked Eric Schmidt, and he went about it very ham-handedly, but I do think he is right. Stopping is not an option given Capitalism's hunger for growth and the current geopolitical landscape. The genie is out of the bottle and we must adapt, because Capitalism is not going to.
>Anyway, just find it strange to be so militantly anti a certain tech.
You know, that's fair. I'm much more against super-rich investing hundreds of billions in the things they don't understand, creating massive disruptions in their wake.
AI didn't create stupidity and greed. In the end, it's just another tech. I'm just tired, time and again, of people who I would hope to know better (and repeatedly they prove me wrong).
Hi Simon; while it's true that the token providers have found that their product is 90% useful to devs and 10% useful to everyone else, this is something they found out in the first quarter of 2025 anyway.
It's not exactly news, is what I'm saying. And even with the PMF they found, the product is still only a commodity i.e `tokens`, which is what every other provider on the planet is also providing.
All their other products boil down to "harnesses", which does not look viable as a product in the sense of PMF - you cannot sell it, you cannot lock it to your own subscription, API, etc. so you can't use it to generate revenue any more than the free harnesses do.
PMF has a specific meaning, and "code harness" or "coding model" does not satisfy the commonly accepted meaning. Maybe Mythos (or similar) will.
Hi simonw, can you write your thoughts (hivemind is yet to catch up with this idea), the idea of distilling a large Opus 4.7 model into a purely reasoning core with plugin like architecture (a programming sub-model, a literature submodel, a history submodel, a geography submodel). Why is Russian and Chinese data part of my model training process, its costs more to train and do inference. I want a core model and specialized models to which Core Reasoning model can talk to. This kind of innovation is what Mistral team should be doing. Is it fundamentally impossible to do?
Who’s an anti-human extremest? Doesn’t that sort of warrant some sort of facts to justify such an extreme position? What makes you feel this is a misallocation of capital OR something…anti human?
1) Daily, there were 2-3 very active ones in my small town. Procomm Plus was what I used the most in DOS. This was also a stepping stone to IRC. It got to the point I was doing chores to pay for a second phone line for my bedroom.
2) The phone numbers were in a little ad box in the newspaper one time.
3) Most people seemed to bounce around to each BBS but there were communities within each that also seemed to stick there. I expect that was partially due to relationships that people had with the sysops.
4) It was a small East Texas town, so people were generally friendly. We were just kids, like 12 years old, having political discussions with adults. People would also trade or offer up gear they had. I remember inviting a high school guy over to my (parent's) house to install a 28.8k modem for FREE because he had upgraded to 56k. He just gave it to me for nothing. As far as I knew people just treated each other like people. I don't recall ever knowing I was being excluded from something because of my age. For a while there were monthly meetups at a local pizza place.
5) I wasn't interested in programming back then. I remember a lot of talk of hardware, mostly modems, one guy trying to convince every Amiga was the future, file sharing/warez (I downloaded Duke Nukem 3D from a BBS in 5MB zip files), chess and other games over FidoNet.
I'd choose a different word for the title of Hoard Things You Know How to Do. Hoarding is the opposite of what we want to do but I get from reading the section you mean create a collection that you can draw upon. IMO "Share" is a much better word choice.
That's what he was saying. Wall Street (the stock market) are people's "pensions" now because everyone has a 401k or equivalent so their retirement is tied to the market. Thus, these companies are betting America's collective retirement on AI...
I thought he was talking about actual pension funds, which still exist and invest large sums of money in Wall Street. But make sure your 401k doesn't include AI funds then. You should have a choice over what part of the market to invest in.
None of these articles address how we'll go from novice to expert, as either self-taught or through the educational system, and all the bloggers got their proverbial "10k hours" before LLMs were a thing. IMO This isn't abstractions, the risk is wholesale outsourcing of learning. And no, I don't accept the argument that correct and LLMs errors is the same as correcting a junior devs errors because the junior dev would (presumably) learn and grow to become a senior. The technology doesn't exist for an LLM to do the same today and there's no viable path in that direction.
Can someone tell me what the current thinking is on how we'll get over that gap?
> I don't accept the argument that correct and LLMs errors is the same as correcting a junior devs errors because the junior dev would (presumably) learn and grow to become a senior. The technology doesn't exist for an LLM to do the same today and there's no viable path in that direction.
But the technology does exist. The proof is in the models you can use today, on two lines:
First, what you describe is exactly what the labs are doing. We went from "oh, look, it writes poems and if you ask for code it almost looks like python" 3 years ago. Since then, the models can handle most programming tasks, with increasing difficulty and increasing accuracy. What seemed SF 3 years ago is literally at your fingertips today. Project scaffolding, searching through codebases, bug finding, bug solving, refactorings, code review. All of these are possible today. And it all became possible because the labs used the "signals" from usage + data from subsidising models + RL + arch improvements to "teach" the models more and more. So if you zoom out, the models are "learning", even if you or I can't teach them in the sense you meant.
Secondly, when capabilities become sufficiently advanced, you can do it locally, for your own project, with your own "teachings". With things like skills, you can literally teach the models what to do on your code base. And they'll use that information in subsequent tasks. You can even use the models themselves for this! A flow that I use regularly is "session retro", where I ask the model to "condense the learnings of this session into a skill". And then those skills get invoked on the next task dealing with the same problem. So the model doesn't have to scour the entire code base to figure out where auth lives, or how we handle migrations, and so on. This is possible today!
You spent the proverbial 10k hours like before. I don't know by AI has to lead to the lack of learning. I don't find people stop learning digital painting so far, even digital painting, from my perspective, is even more "solved" than programming by machines.
I heard that Pixar had a very advanced facial expression simulation system a decade ago. But I am very willing to bet that when Pixar hires animators they still prefer someone who can animate by hand (either in Maya or frame-by-frame on paper).
I can tell you the current thinking of most of the instructors I know: teach the same fundamentals as always, and carefully add a bit of LLM use.
To use LLMs effectively, you have to be an excellent problem-solver with complex technical problems. And developing those skills has always been the goal of CS education.
Or, more bluntly, are you going to hire the junior with excellent LLM skills, or are you going to hire the junior with excellent LLM skills and excellent technical problem-solving skills?
But they do have to be able to use these tools in the modern workplace so we do cover some of that kind of usage. Believe me, though, they are pretty damned good at it without our help. The catch is when students use it in a cheating way and don't develop those problem-solving skills and then are screwed when it comes time to get hired.
So our current thinking is there's no real shortcut other than busting your ass like always. The best thing LLMs offer here is the ability to act as a tutor, which does really increase the speed of learning.
Thanks for the response, I appreciate it. I absolutely agree with you about CS education. I went to school to learn how to learn. So, the best-case outcome is everyone has A Young Lady's Illustrated Primer available to them. At that point I suppose to really does live with the individual as to whether they want to see how much potential they really have.
Agreed. If someone could help answer the question of "how" I'd appreciate it. I'm currently skeptical but not sure I'm knowledgeable enough to prove myself right or wrong.
But, it just seems to me that some of the 'vulnerabilities' are baked in from the beginning, e.g. control and data being in the same channel AFAIK isn't solvable. How is it possible to address that at all? Sure we can do input validation, sanitization, restrict access, etc. ,etc., and a host of other things but at the end of the day isn't it still non-zero chance that something is exploited and we're just playing whack-a-mole? Not to mention I doubt everyone will define things like "private data" and "untrusted" the same. uBlock tells me when a link is on one of it's lists but I still click go ahead anyways.
At least in its current state we just use an LLM to categorise each individual tool. We don't look at the data itself, although we have some ideas of how to improve things, as currently it is very "over-defensive". For example, if you have the filesystem MCP and a web search MCP, open-edison will block if you perform a filesystem read, a web search, and then a filesystem write. Still, if you rarely perform writes open-edison would still be useful for tracking things. The UX is such that after an initial block you can make an exception for the same flow the next time it occurs.
Thanks for the follow up. I can see the value in trying to look at the chained read - search - write or similar patterns to alert the user. Awareness of tool activity is definitely helpful.
It is possible to configure it like that - when a trifecta is detected, it is possible for the gateway to wait for confirmation before allowing the last MCP call to proceed. The issue with that MCP clients are still in early stages and some of them don't like waiting for a long time until they get a response and act in weird or inconvenient ways if something times out (some of them sensibly disable the entire server if a single tool times out, which in our case disables the entire gateway and therefore all MCP tools). As it is, it's much better to default to returning a block message, and emit a web notification from the gateway dashboard to get the user to approve the usecase, then rerun their previous prompt.
Because you mentioned the use case specifically, I wanted to point you to the fact that Excel has been able to convert images to tables for a while now. Literally screenshot a table from your PDF and it will convert to table. Not trying to diminish any additional capabilities you're getting from Gemini, but this screenshot to table feature has been huge for my finance team.
Honestly I think you might be grappling with getting older and the change that naturally comes with it.
>I've let many of my most meaningful friendships fade.
At least you acknowledge that part and aren't bitter at your friends that it is somehow their fault.
>but it doesn't feel like when I was in college and hung out with a crew of 10+ people on a weekly basis
And it won't, ever again. They'll get married, move away, have kids, whatever. Just like if you played a sport in high school, or were in the band, that same group of people will never be together doing that same activity again after the last time.
>curated events and meaningful connections for men who don’t want their friendships to atrophy post-college
Except you acknowledge above your role in the "atrophying" and while you can say you didn't/don't want that to happen, you still allowed it to didn't you?
>The goal is to get people in the same place on a consistent basis.
Isn't that called the gym, the range, the golf course, softball/kickball/pickle ball team, bar, etc? I've struggled (still?) with exactly this thing as well and don't have any good advice. I will say it feels related to the notion of wanting to have a significant other but never leaving the house, you gotta put the effort in. On the bright side I read an article about a couple that missed neighborhood connections so started having coffee on their porch on Saturday mornings (or some consistent day of the week) and eventually neighbors walking by started saying hello, then stopping to chat, then bringing their own coffee, and then it became this whole neighborhood thing. So I guess I'm saying don't lose hope that you can't change things in your situation.
You're definitely on to something. Although early 30s doesn't seem so old, the intense nostalgia of college has definitely waned. I would say I'm more grappling with the reality that it really won't ever again feel like that. I know it's true from a time perspective... I'm married and have a full-time job. But I figured I couldn't let the dream die that easily :)
Do you really develop lasting friendships on the course or in rec league sports? I just haven't had that experience and the popularity of those activities is sky rocketing (see: running clubs) while the problem doesn't seem to be getting any better.
> Do you really develop lasting friendships on the course or in rec league sports? I just haven't had that experience and the popularity of those activities is sky rocketing (see: running clubs) while the problem doesn't seem to be getting any better.
When I did rec league sports most of the guys were there to meet women
That’s what I notice with a lot of meetups, etc. guys don’t even want to talk to other guys, they gotta talk to women only, personally I’ll talk to whoever
I think you can develop lasting friendships doing pretty much any group activity. But it can require a lot more effort (perhaps on your part) to get the ball rolling. Depending on the activity, you probably won't be having deep (or any) conversations while doing the activity, so you need to actively engage with people before or after the activity. That might be very small at first, but over many weeks or months might grow into grabbing a drink or meal after the activity, and being open to starting deeper conversations.
I'm terrible at this. I struggle to push myself to ask deeper questions of new friends, feeling like I'm being intrusive or prying, but I think it's necessary to do this in order to move forward. When we were in college, making friends was easy, because there was a shared experience right in front of us to talk about, and that could naturally lead to deeper conversations. As we get older, that isn't really there, and it takes active, deliberate effort to get there.
I think to the parent's point it is as you say: there is already untapped capacity that isn't being used due to (geo)political forces maintaining the scarcity side of the argument. Using your agriculture example, a simple Google search will yield plenty of examples going back more than a decade of food sitting/rotting in warehouses/ports due to red tape and bureaucracy. So, we already can/do produce enough food to feed _everyone_ (abundance) but cannot get out of our own way to do so due to a number of human factors like greed or politics (scarcity).
And that sort of analysis is exactly what is suspect to me about this. Have people considered why an onion might be in a warehouse or why it might go unsold after a time? The answer is no and reveals a lack of understanding of nuance of how the global economy actually works. Everything has some loss factor and removing it all to nill might not be realistic at all at the scale we do things to feed ourselves. Its like making pancakes: some mix stays in the bag you can’t get out, some batter stays on your bow, some stays on your spoon, you make pancakes with some, some scrap is left in the pan, some crumbs on your plate. All this waste making pancakes and yet to chase down every scrap would be impossible. And at massive scale that scrap probably ads up.
Besides we are crushing global hunger over the decades so something is working on that front. The crisis in most of the western world today at least is that merely wages are depressed compared to costs for housing (really land) versus not being able to afford food.
https://web.archive.org/web/20080930065642/http://www.whywor...
"I [Bob Black] don't suggest that most work is salvageable in this way. But then most work isn't worth trying to save. Only a small and diminishing fraction of work serves any useful purpose independent of the defense and reproduction of the work-system and its political and legal appendages. Twenty years ago, Paul and Percival Goodman estimated that just five percent of the work then being done -- presumably the figure, if accurate, is lower now -- would satisfy our minimal needs for food, clothing and shelter. Theirs was only an educated guess but the main point is quite clear: directly or indirectly, most work serves the unproductive purposes of commerce or social control. Right off the bat we can liberate tens of millions of salesmen, soldiers, managers, cops, stockbrokers, clergymen, bankers, lawyers, teachers, landlords, security guards, ad-men and everyone who works for them. There is a snowball effect since every time you idle some bigshot you liberate his flunkies and underlings also. Thus the economy implodes."
>"These are tools which burn vastly more tokens, but are also quickly becoming daily drivers for the work carried out by extremely well-compensated professionals."
>"Somehow this fragment turned into headlines like Uber’s COO says it’s getting harder to justify the money spent on AI tokenmaxxing, because the market for stories about AI failures remains enormous."
Yes, it's just the yearning for AI failures. It couldn't possibly be runaway costs, record revenues, and massive layoffs. It couldn't possibly be that these tools are lighting dollars on fire by people already paid significantly well and not producing any increase in "value" for it (I recognize that output is 100x but outcomes are flat by all measures).
[1] https://cmr.berkeley.edu/2025/10/seven-myths-about-ai-and-pr... [2] https://futuretech.mit.edu/publication/crashing-waves-vs-ris...