Earlier quoted context omitted.
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.
Oracle and some company wide Microsoft licenses.
Uber's $1,500/month AI limit is a useful signal for AI tool pricing
561–570 of 819 posts
Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing
#562Earlier quoted context omitted.
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…
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 m…
Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing
#563Earlier quoted context omitted.
One aspect Paul Kedrosky mentioned recently is the concept of „duration mismatch“. The price per token goes down over time (either because the AI vendor reduces due to competition pressure, or because customers are now incentivized to use older cheaper models). But datacenters are financed through debt, with the assumption their revenue increases over time. Quoting him: „[AI vendors are] paying for a fixed cost with…
"So you have on one end the token revenue trending down, on the other end the training cost going up for the next frontier models, and you need to pay back your 10y debt." Not necessarily, the bond holders could simply take a massive hair cut and lose shitloads of money. On the topic of bubbles and exuberance, Jeff Bezos made the salient point that there was a massive over-invested biotech boom in the 1990s and tons…
Drugs cost pennies to manufacture after they are researched and make their way through the approval pipeline. There are many generic drug manufacturers who can work off the existing formulas.
The more apt comparison is that LLMs won't be un-trained. Opus 4.8 now exists. Even if Anthropic somehow went bankrupt, that particular asset could, at the very least, be sold for proverbial pennies on the dollar to a "generic" inference provider.
Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing
#564Earlier quoted context omitted.
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.
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…
At my company we can ask for temporary cap limits if it’s justified, which is fairly common.
Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing
#565Earlier quoted context omitted.
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.
Oh, it won't get any better. LLMs already trained on every bit of code ever published, they won't get any more material.
Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing
#566Why 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?
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.
Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing
#567Why 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?
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.
Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing
#568Earlier quoted context omitted.
Those companies are certainly writing more code. But It isn’t clear that they are increasing their economic productivity. It could even conceivably have the opposite effect by fueling a race to the bottom. e.g. an interesting possible canary in this coal mine is that there’s been a 200% increase in the rate of new apps appearing on Apple’s App Store, but it has not been accompanied by a 200% increase in the rate at w…
That’s great for consumers.
Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing
#569Earlier quoted context omitted.
Companies whose main core competency is writing code were already making up a big chunk of the economy before AI. Also, less wealthy companies were constrained in their use of software by the inability to afford the salaries of talented programmers (and ripoff practices from software consulting companies who in theory could help). Lowering the cost of building software systems ought to unblock a good amount of econom…
Those companies are certainly writing more code. But It isn’t clear that they are increasing their economic productivity. It could even conceivably have the opposite effect by fueling a race to the bottom. e.g. an interesting possible canary in this coal mine is that there’s been a 200% increase in the rate of new apps appearing on Apple’s App Store, but it has not been accompanied by a 200% increase in the rate at w…
I don't believe this aligns with the reality of any major company, unless your business is in the literal sense "selling code" your revenue and profit is tangential to the quantity of code you produce. Google is a good example of this: most of their revenue and profit comes from their ad network, which is disconnected from their development productivity and instead heavily reliant on network effects and time in market. If I was a new competitor with infinite AI funds to throw at whatever problem I choose, I can't simply capture their market by developing an exact copy of Google's ad platform. In the same way, Google can't substantially grow their ad network by coding "more" or "better", they still need more customers and consumers to interact with their network to see any increase in revenue.
So it doesn't directly follow that a productivity increase will inherently follow an AI usage increase.
Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing
#570Earlier quoted context omitted.
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.
When you criticize AI, always remember that the alternative is the average employee. Today's models are pretty good.