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Uber's $1,500/month AI limit is a useful signal for AI tool pricing

simonwillison.net

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Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#81

Post by jbvlkt »

onlyrealcuzzo wrote: post #44
ashahin wrote: post #36

[flagged]

It's interesting to me how ineffective LLMs are at refactoring, but when you think closely about how they work, it makes sense. They are good at searching for things that have been done 10,000 times before, and slightly changing them. This is the majority of all "new" features. Almost nothing is "new"... Refactors are not this. If you can't just write a gsub to do the work, they need to essentially break it up into N…

Exactly my experience. I always refactor first myself then delegate boring tasks to AI. It saves me energy, time and also tokens. If code is not prepared for easy implementation agents always fail.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#82

Post by slopinthebag »

nonethewiser wrote: post #53
jcgrillo wrote: post #20

Earlier quoted context omitted.

> WTF did Uber build with all of that spend? WTF did anyone build with all that spend? Despite all the feel-good anecdotes about how productive folks feel using ai coding tools there's a deafening silence when it comes to actual, demonstrated efficacy. How can we be this far entrenched in these workflows and still not know whether they actually do anything useful?

The real answer? Software engineer quality of life. There can be an increase in productivity without a corresponding increase in total output. The gains could be captured by software engineers doing a days work in an hour then fucking off in a variety of ways.

Yeah I think this is probably most accurate.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#83

Post by treis »

jvanderbot wrote: post #30
CharlieDigital wrote: post #4

$1500/mo is $18,000/seat/annum. Maybe Microsoft and Nvidia are on to something. 128 GB machines that can run local LLMs are a bargain even if priced $5-8k. Yes, tok/s is not quite there, but that's probably OK since the bottleneck really isn't the code; it's WTF did Uber build with all of that spend? How did it meaningfully impact their revenue in a positive direction?

Right - the future of LLMs is like ol' windows XP+Dell. Commercialized "things" you run locally offline, co-designed with hardware, with a known productivity suite, and large businesses building the next generation thing and suite with 18mo release cycles (ish).

I don't see it. Leasing equipment and paying per seat license fees makes a lot of accounting and cash flow sense. Maybe when it gets to the point where you can run SOTA LLMs on consumer hardware. But that seems a solid decade and probably much more away.

Even then it makes more sense to rent the bigger GPU and get your answer faster.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#85

Post by skybrian »

mrweasel wrote: post #75
dkdcdev wrote: post #16

Earlier quoted context omitted.

at their scale they could also just run a large on-premise or rented (basically still cloud, but cheaper) GPU cluster and run through that. fixed costs, even license a SOTA model’s weights if you’d like

The problem isn't really Uber, Microsoft or Nvidia, it's all the smaller none IT companies that also have developers on staff. They are screwed. $1500 per seat per month is just way to expensive, but they also can't afford to build and maintain their own on-premise solution. If Microsoft can't afford to run CoPilot for their own developer, what chance does any of their customers stand? If the large, well founded IT c…

It's an extra 18k a year for developer tools when they're paying how much a year per developer? Having software developers at all isn't cheap.

Also, I don't believe you need to spend $1500 a month on a coding agent if you optimize usage at all.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#86

Post by izacus »

jcgrillo wrote: post #50
awesan wrote: post #27

Earlier quoted context omitted.

I can say at least for me at a small-ish company (~40 FTE) there has been a surge in internal productivity tools. Nothing to improve the end user product directly but a lot of tools to make processes easier and less error prone. What would previously be janky internal dashboards or excel sheets are now actually nice to use tools. That said of course the maintenance cost of all that has yet to be discovered, and the R…

Yeah this seems to be a pretty widespread story, from what I've heard as well. The thing about those janky dashboards and spreadsheets though is that somebody understood them and built them with intent to solve a particular problem. Despite the rickety appearance, they're trustworthy tools. A polished single page app might look nicer but it's harder to debug than an excel sheet, and much less transparent in its inter…

More importantly, it's questionable how much extra revenue improving a design of internal tool brings.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#87

Post by treis »

mrweasel wrote: post #75
dkdcdev wrote: post #16

Earlier quoted context omitted.

at their scale they could also just run a large on-premise or rented (basically still cloud, but cheaper) GPU cluster and run through that. fixed costs, even license a SOTA model’s weights if you’d like

The problem isn't really Uber, Microsoft or Nvidia, it's all the smaller none IT companies that also have developers on staff. They are screwed. $1500 per seat per month is just way to expensive, but they also can't afford to build and maintain their own on-premise solution. If Microsoft can't afford to run CoPilot for their own developer, what chance does any of their customers stand? If the large, well founded IT c…

There's models for every price point. What was SOTA and stupid expensive to run a year ago is a cheap flash model today.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#88

Post by Igrom »

simonw wrote: post #49
jkwang wrote: post #9

The $1500 number is less interesting than the fact that they hit a ceiling at all. Most engineering teams I've talked to have no idea what their AI spend is per developer because it's buried in a consolidated cloud bill. Having a hard cap forces two useful conversations: what workflows actually justify API calls vs local inference, and whether the output is being measured against any real productivity metric. Without…

Both the Anthropic and OpenAI "Enterprise" plans include per-developer analytics: Anthropic: https://support.claude.com/en/articles/12883420-view-usage-a... OpenAI: https://help.openai.com/en/articles/10875114-workspace-analy...

I believe you might be replying to a bot account.

Re: Uber's $1,500/month AI limit is a useful signal for AI tool pricing

#90

Post by FergusArgyll »

darkwater wrote: post #24
CharlieDigital wrote: post #4

$1500/mo is $18,000/seat/annum. Maybe Microsoft and Nvidia are on to something. 128 GB machines that can run local LLMs are a bargain even if priced $5-8k. Yes, tok/s is not quite there, but that's probably OK since the bottleneck really isn't the code; it's WTF did Uber build with all of that spend? How did it meaningfully impact their revenue in a positive direction?

> it's WTF did Uber build with all of that spend? You can ask the same for the median 330k salary in the US for Uber Engineering... and being a bit snarky, attending Uber engineers talks here and there at a few conferences, looks like. they love to (re)invent internal tooling/platforms. That's pretty expensive on its own. EDIT: I'm not saying that Uber's engineers didn't add value to the company, they absolutely did…

This is a very good answer but there's a flip side too.

The idea of "if you add intelligence you make more money" is contradicted by the fact companies don't just always hire more people. Wy doesn't google just hire everyone?

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