Uber president says AI spending is getting 'harder to justify'

https://www.theverge.com/transportation/937116/uber-ai-investment-hard-to-justify

by berlianta • 2 months ago

304 158 2 months ago

chollida1• 2 months ago

I do find it to be true that with coding agents the famous quote from Jurassic Park goes through my head multiple time a day

"our scientists were so preoccupied with whether they could, they never stopped to ask if they should.

I've now come to the realization that if I'm having an llm work constantly all day writing code for me i'm probably doing something wrong as I'm no longer focusing on the core issue itself.

I may be in a minority here in that I write code to augment my self and not to ship to others so I can tell very quickly if I'm just gold platting something or if i'm actually delivering real value to my trading or risk management.

kshri242• 2 months ago

I still get picked up by an Uber the same way. As an end user, nothing has changed for me.

So I wonder what the heck were all those billions of AI tokens burnt on that they extinguished it in just 4 months into the year?

fancyfredbot• 2 months ago

Apparently:

* In App Hotel bookings in partnership with Expedia.

* Travel Mode with suggestions on where to eat and visit when travelling.

* Eats for the way - your driver picks up a takeaway for you to eat while they drive you to your destination.

* Voice bookings using AI and speech to text.

How did we ever live without them!

burkaman• 2 months ago

Eats for the way - your driver picks up a takeaway for you to eat while they drive you to your destination.

This seems like the kind of terrible idea that an LLM might have come up with. I'm pretty sure most drivers do not want people eating (especially a whole meal) in their car, and I can't imagine a lot of instances where you're calling an Uber and don't have time to get yourself food, but don't mind waiting an extra 10 minutes for the driver to detour, find parking, and wait for your food.

newaccountman23• 2 months ago

Holy fuck, aside from the voice bookings, that's some useless shit to spend money building as far as both tokens and salaries go.

Are they profitable yet lol

fg137• 2 months ago

For context, this is an interview where Uber CEO discussed these ideas:

https://www.theverge.com/podcast/922909/dara-khosrowshahi-ub...

Can't say I am convinced.

Aurornis• 2 months ago

This argument is funny because you could have said the same thing 4 years ago: Uber still picks you up just as it did years before that, so what did all those millions spent on developer salaries get them?

Uber’s business is relentlessly confusing for people who think it’s a simple app to send an alert to a nearby driver to pick you up.

Uber operates at a scale where there are no trivial problems because even small changes can impact hundred of thousands of customers. They can also justify spending time and money on new features that only 0.1% of customers might use because 0.1% of their customers is a very large number.

thewebguyd3• 2 months ago

Uber also has to maintain thousands of region specific rules and features to be able to operate globally, and they do it all in the same app instead of having specific regional versions (which would be a terrible user experience for frequent travelers). That alone is a ton of work the end user will never see but is core to their operation.

kshri242• 2 months ago

This is not just me saying it. The Uber president himself says it in the article.

so what did all those millions spent on developer salaries get them?

There was no doubt about what these developer salaries got them. It was to keep Uber stable and running in thousands of jurisdictions with varying rules/regulations.

The idea of using AI was (I hope) not just to replace developers for this purpose but to also ship features/products beyond what was already being offered. It has however not panned out as these CEOs/execs thought it would.

They can also justify spending time and money on new features that only 0.1% of customers might use because 0.1% of their customers is a very large number.

And what are those features exactly? Because even the President of Uber doesn't seem to know:

"“That link is not there yet, right? I think maybe implicitly there is more that is getting shipped, but it’s very hard to draw a line between one of those stats and, ‘Okay, now we’re actually producing 25 percent more useful consumer features,’” said Macdonald."

The budget allocated to AI for the year has been wiped out in 4 months.

tayo42• 2 months ago

There's probably tons of backend projects going on, expanding in countries, payments, complying with regulations, effeciency and reliability projects. They also do food delivery. There's a whole engineering team to support

deaton• 2 months ago

Goodhart's law strikes again. Stop giving your engineers token-burning quotas or they'll burn tokens.

dangus3• 2 months ago

I really don’t understand on the customer side of B2B why so many companies actively encouraged AI tooling costs.

I can understand it from the side of the companies selling tokens and AI hardware. I don’t understand the race to spend more on internal tools.

I’ve been sitting around waiting for my company to buy a number of necessary bits of tools. They cheap out on every solution imaginable. Datadog is too expensive, let’s buy a cheap solution that costs us months of setup time. Configuration management is too expensive, let’s use the free version with no audit trail or dashboard.

But everyone…in the entire company…gets multiple AI tool subscriptions.

I don’t remember investors being this stupid at any other point. I don’t recall investors pressuring my company to use blockchain or NFTs.

xingped• 2 months ago

Nothing that C-execs and management advocates for has made any sense for a long time now. If this is the first you're starting to question it all, I must ask what rock you're sleeping under because I desperately need a really good nap...

pjmlp• 2 months ago

I surely remember everyone does SOA, everyone does NoSQL, everyone does Hadoop, everyone does microservices, everyone does kubernetes,....

Not with the same pressure as everyone in the company (literally everyone, regardless of the job role) has to burn AI tokens, and attend forced AI workshops, still it is always running after the next new shinny.

ambicapter• 2 months ago

Nobody wanted to admit that they had no idea how "AI" was going to help but nobody wanted to get left off the hype train...so they tasked their engineers to figure something out...by just asking them to spend as much as possible (As I explain this it just sounds stupider and stupider). Of course, spending willy-nilly is not a good way to find a profitable (or smart) idea, but that's a problem for future company bottom line.

kevincox• 2 months ago

The logic is quite simple. Management thinks that AI can improve productivity, but knows that there will be some resistance and some learning curve. So they force people to use it so that people can 1. develop their skills and workflow and 2. find out where it is useful 3. find out what needs to be improved to make it useful.

As a more obvious example consider that cars were just invented and the post office management thinks that they could improve performance of letter carriers. But right now cars are slow, break down a lot and there isn't much infrastructure for them. Lots of letter carriers will (rightly) think that it is a waste of time because they need to get in, stop, park between every house and they break down so often it isn't worth it and half of their route is unsuitable for a car anyways. But if cars are forced for a while they will find out what routes work well for cars and which don't, improve the cars and related infrastructure to make cars more effective and other improvements to unlock more productivity.

So yes, right now management is wasting money on cars and gas for no increased productivity. And yes, measuring how much gas each employee uses and encouraging to use more is obviously stupid in isolation. But the idea is to force adoption to iron out the kinks and find out where it can improve productivity. It is basically funding a research project.

xnx• 2 months ago

Dupe: https://news.ycombinator.com/item?id=48268871

berlianta• 2 months ago

go ahead

sbmthakur• 2 months ago

Affordable inference will be around longer if more Big tech companies cap their AI sending.

Mistletoe2• 2 months ago

It feels like maybe the wheels are starting to fall off the AI hype train. I expect complete collapse once people start figuring out that the numbers on all this don’t make sense. I’m looking for investment portfolios that will weather that storm. If you are reading this and have a similar curiosity, this is a great place to start.

https://portfoliocharts.com/2021/12/16/three-secret-ingredie...

rtkwe3• 2 months ago

I've been thinking that for years about various sources and the bubble stubbornly refuses to pop on a convenient timeline so I'm falling back on the adage "time in the market beats trying to time the market". Index funds and chill is much more relaxed than trying to determine who's actually going to survive the AI bubble popping.

DesiLurker2• 2 months ago

this is the reason I refuse to budge from my index portfolio besides small 'play money' ventures. My investing philosophy is basically by the time it hits wire you dont know what portion of it factored in. especially in age of AI and automation IMO alpha will vanish faster as anyone can code up eqv of a bloomberg terminal themselves. So all thats left is how do you manage downturns, when market heads down 30% but your handpicked stocks go down 60% you need to have enough wherewithal to hold through bad times. this is where true test of faith comes, I believe I would be cowardly and sell out at wrong time. So its best to just hold index and market sort the bloodbath out itself.

ericmcer• 2 months ago

Market makers are not going to let anything collapse, there is not going to be a "storm".

The government and everyone with any money/power are fully invested in keeping the market going regardless of any kind of reality.

"Every American child under 18 with a Social Security number can have a federally recognized "Trump Account," a one-time $1,000 IRA seed deposit"

By doing this every citizen will personally have skin in the game and want markets to continue to rise.

Mistletoe2• 2 months ago

So what you are saying is “this time it’s different”. That’s a dangerous thought to have.

https://www.currentmarketvaluation.com/models/s&p500-mean-re...

ex-aws-dude• 2 months ago

What has been the end result of all the tokens companies are burning?

Where does it show up in quarterly results?

I can’t see how it’s sustainable just based on “this feels more productive”

zitterbewegung• 2 months ago

Advancement in AI research seems to be the only thing at this point.

bitwize• 2 months ago

Where does it show up in quarterly results?

Standard answer is "companies that are not seeing significant gains from AI just aren't AI-ing hard enough, trust me bro".

gizajob• 2 months ago

In the big red number shown after revenue where profits used to be.

joenot4433• 2 months ago

A friend of mine added some pretty extensive iOS UI tests to a keystone feature hit by millions every month. They'd been kicking the can down the road for years, trying to fit it in their roadmap, and with Claude running overnight they were able to bang out the whole suite in a week.

I'm not sure how it would show up in quarterly results.

dotancohen2• 2 months ago

  > I'm not sure how it would show up in quarterly results.

Technical debt is famously difficult to express in either layman's terms or financial terms.

smelendez2• 2 months ago

I see these kinds of stories here a lot, and I'm curious whether they reflect a steady stream of need for AI coding, or whether a lot of companies have a burst of AI-appropriate coding work now that the technology is available and then will have a smaller need going forward.

Is it like the stereotypical dad who rents a power washer, powerwashes every exposed surface on his property, and then doesn't need to do any powerwashing for a few years; his neighbor who gets an Instant Pot and uses it for every meal for a month, then sees it gathering dust when the family gets tired of pressure-cooked stews; or like their neighbor who gets a microwave oven and uses it multiple times a day for decades?

I guess only time will tell.

rtkwe3• 2 months ago

In my limited experience with using agents to create tests it tends to code the tests to the existing code instead of ensuring the correctness from a spec. Great for regression testing but still limited in effectiveness for catching existing issues.

levkk• 2 months ago

It wouldn't, at least not directly. That's why it wasn't done pre-AI.

ElFitz• 2 months ago

Over here our CTO replaced Intercom with an internal equivalent that costs less than $20 / month to run, haiku and sonnet support agent costs included. In less than a few weeks, in his spare time.

jayd16• 2 months ago

Probably shows up in OpenAI and Anthropic quarterly reports. I have to wonder if that was the point.

Legend24402• 2 months ago

Even if Uber really did double developer productivity, would it translate to quarterly results?

Ultimately they make money selling rides, not selling software. The Uber app is mature and adding new features is unlikely to significantly increase sales.

Writing 2x more code doesn't translate to 2x more revenue unless it results in 2x more rides.

mattnelson• 2 months ago

Lowering costs to run the infra would show up as increased profits without any change in rides.

afavour• 2 months ago

Even if Uber really did double developer productivity, would it translate to quarterly results?

It would if it meant they then fired half their software engineers, which is the ultimate goal.

nlawalker• 2 months ago

I never took tokenmaxxing to be about improving productivity directly; mundane feature work that comes out of it is just a side effect. I always saw it as a race between these big tech companies to get a generational advantage by being the one to discover the way of the future, with respect to harnessing AI to actually and truly automate software development.

EDIT: whoa, I used "way of the future" as a reference to Howard Hughes in "The Aviator", not this Way of the Future religious organization thing I just stumbled on; no intended reference there.

infecto• 2 months ago

Agree and I have wondered behind close doors if this is not the mental model. You need to spend money to see what is working this was simply a way to see that.

lazide2• 2 months ago

Eh, I also saw it as a rather blatant attempt to undermine the bargaining power of the Software Engineer (which had grown to insane proportions over the years) - both in working conditions and raw cash money.

In many cases it really didn’t/doesn’t matter if the AI automation actually works, just that people think it could - and hence leave money on the table.

lenerdenator2• 2 months ago

insane

Not sure if you mean this in a good or bad way.

izzydata• 2 months ago

My impression of companies pushing AI so heavily is that they are basically being forced to do it by it merely existing. Imagine if AI really is as powerful as it is suggested to be and you didn't jump on the bandwagon. Then you would be behind. So by it existing and other companies using it, you have to as well because even if it turns out to be a failure at least everyone else will have failed too and you are on an even playing field.

jrmg2• 2 months ago

You could kind of use that line of thinking to justify spending on anything.

stephen_cagle• 2 months ago

I feel like this is kind of like the gambler's risk of "going bust" but applied backwards?

Feels like it would be better to spend just enough so that you have the capacity to scale up IFF LLM's end up being a big deal. You spent less than your rivals (who were competing for a supremacy that never came), but you have saved more "dry powder" to compete against them for the more likely future. The only future you exclude with this strategy is the "LLM Supremacy" future, which you only had a 1/(number_of_players) chance of winning anyway. :]

I think the real reason for the spending is that the scent of LLMs in the air causes stock values to go up. And even if everyone knows it does not make sense, they still want "NUMBER GO UP", and so they will spend more money to excite the amateur and professional investor class.

jaredklewis• 2 months ago

This is insightful. It does sort of feel like the search for the Northwest passage.

tracerbulletx• 2 months ago

Yeah this is right. Its about taking the throttle off of experimentation hoping some team suddenly starts shipping a years worth of features in a week and responding to strategic customer demands in near real time. Then copying what works out across the org. (and probably downsizing)

groby_b• 2 months ago

What those organizations miss is that they drown their teams in organizational red tape. The way to the future isn't tokenmaxxing - it's cutting back on process noise.

nobodyandproud2• 2 months ago

My hot take: The way of the future is local LLMs.

The AI equivalent of the PC revolution isn’t quite here yet, but it’s the only way forward.

charcircuit• 2 months ago

It will always be worse compared to a centralized approach where hardware utilization can remain high. Except in case which demand low latency which most development things do not need. It's okay if it takes an extra 100ms for a code review to take place.

garrickvanburen• 2 months ago

I agree. We don't need a nondeterministic 10quadrillion vector model. We need an deterministic expert on our narrow business. Something small, that can be run on the 2026 version of the spare PC under the CTOs desk.

hintymad• 2 months ago

by being the one to discover the way of the future

This is my understanding too. The underlying assumption is that action leads to information, iterations lead to enlightenment. So from an org's point of view, tokenmaxxing means encouraging everyone to explore as much as they can. Of course, token volume should not be the only metric - tokenmaxxing is just a catchy phrase.

butlike• 2 months ago

action leads to information, iterations lead to enlightenment

So doing something (action) creates something new (more information), and iterating on that new information leads to the realization there is nothing new left to be learned with that information (enlightenment). Is how I'm interpreting that.

layer8• 2 months ago

To the extent that figuring out the true automation will lead to layoffs, that knowledge will quickly spread as the laid-off knowledge workers are available for hiring.

rixed• 2 months ago

Like many corporate behaviors I believe we tend to rationalize them too much. Most job posts for management ask for previous experience with "implementing AI". Managers don't want to be left out any more than devs. Devs rewrite everything in the language-du-jour, managers max out tokens.

dwa3592• 2 months ago

I am not sure how uber is operating internally around the use of tokens but if they actually shipped features faster than before then it is still a win. if they learn that users don't want these features or want a different version of it; they have learned this new knowledge faster than they would have if they manually coded those features, which means in principle you should be able to iterate faster. but this will collide with creative ceiling that humans exhibit in a span of time and on top of that uber is prioritizing spending money on tokens over humans which seems like a mistake. you need humans for creativity.

kllrnohj• 2 months ago

I used Uber for the first time in like 8 years recently, and near as I can tell it's the exact same thing it was. What features are they even adding at all much less that anyone cares about? You ask for a ride to a place, a driver shows up, money is exchanged - the end?

Sometimes things are actually just finished. They don't need to treadmill.

datadrivenangel• 2 months ago

They have to make it easier for ubereats orders to have parts of their bill attached to a corporate card and half attached to someone's personal card and be able to split the invoices!

surgical_fire• 2 months ago

if they actually shipped features faster than before then it is still a win

Depends on the cost

redhale2• 2 months ago

This is "Feature Factory" thinking, and it is usually not ideal. Feature count is a poor metric to optimize against. Instead, ROI and delivered customer value should be the focus of product development investments.

louiereederson• 2 months ago

Anthropic's annualized run rate is >$40b according to outside reporting. AWS hit that by Q4 2019. There were still debates on public cloud vs on prem at that time, but by late 2019 public cloud had facilitated the creation or adoption of entire categories of software within SaaS and PaaS, not to mention consumer internet businesses like Uber and Airbnb. The net impact of AI coding tools is far more ambiguous in comparison.

The profitability comparison is fraught but worth noting that by then AWS was already extremely profitable.

testbjjl• 2 months ago

Amazon was AWS first customer. I sometimes feel if the AI companies promises of their models replacing all SWE, they would be a top 3 product/service in any number of businesses and not selling shovels to miners.

electroly• 2 months ago

Amazon was AWS first customer

It wasn't. The retail business took years to move to AWS. They could not even be described as early adopters of AWS.

marrone12• 2 months ago

But they do use their models internally quite a bit. Claude code head talks about how he doesn't write any code himself anymore and just uses agents to do everything. So they are using it themselves.

alfiedotwtf3• 2 months ago

”AI models will replace software developed in 6 months”

— CEO of Anthropic, the employer of over 2000 developers, over 6 months ago

johnbarron• 2 months ago

Anthropic will not have as many husbands as they think by next year: https://xkcd.com/605/

shay_ker• 2 months ago

hot take: token spend can be used a honey pot, especially when compared to what you deliver. spend accordingly!

rowanseymour2• 2 months ago

Now feels like a very good time to be a small team of experienced developers who can largely work on stuff by themselves and not a corporation of hundreds of developers of varying abilities all now trying to show how much code they can generate and how many tokens they can burn.

dylan6042• 2 months ago

Even small teams are not immune from the AI push. I work in a small <10 people with 3 devs. I'm the only one not using AI while receiving push that I'm a problem for not. To the point, VP of company says if we don't all start using AI we'll be out of business because other people will. :face-palm:

niwtsol2• 2 months ago

You don't use AI at all? What is your main justification for not?

foldr• 2 months ago

I think the jury’s still out on how big an impact AI will have on overall, average productivity. But it’s definitely a productivity boost for someone who’s capable of writing code without it. If you want to be super conservative, don’t even have it write any code. Use it to search through existing codebases, review your code, find the root cause of bug reports, evaluate pros and cons of alternative approaches, etc. etc. You’re really missing out by not using it at all.

Here’s a concrete example of conservative AI usage: I use Claude to vibe code my nvim config. Now, who cares if my nvim config is AI slop? What’s the worst that can happen? Nvim works for me now way better than it ever did when I was limited by the time I was willing to spend configuring it manually.

rowanseymour2• 2 months ago

To be clear I meant it's good to be small team on the assumption that we're all using AI... I honestly can't imagine not using AI in May 2026.

sscaryterry• 2 months ago

He could be wrong, but in my opinion, he is probably right. Others are, and will be using AI.

niwtsol2• 2 months ago

100% - I think that is also part of the divide you see online. Devs who work on massive codebases w/ 100s of engineers and see the bugs the LLMs create vs devs who work on smaller codebase w/ small <5 person team.

aantix• 2 months ago

It's a tradeoff.

Generating a feature that is 90% correct in a tenth of the time is a reasonable tradeoff if you're trying to gain traction.

Generating a feature that is 90% correct in a tenth of the time, risking a multi-billion-dollar business, is a terrible tradeoff.

juancn• 2 months ago

There's also the issue that in any large-ish org, code production is hardly ever the bottleneck.

jolt42• 2 months ago

I like the qualification of "large-ish". When someone says code is not the bottleneck, I assume they work for a large company. To be fair, at a start-up developers think they code at least 4 hours a day, but it never averages that either.

DesiLurker2• 2 months ago

I actually think Chinese models have already popped the bubble, we just dont see it yet. the only way to justify AI IPO market cap is basically if they get to hold most sw industry code hostage and then token-flate budgets to collect AI tax. short of that AI expense would very quickly mean revert to model + some margin. this means the moat for AI 'trillion club' is gone. In fact AI virtually guarantees that there is no execution-moat left anywhere, definitely not in code or that engineer with knowledge about that obscure mechanism. without the moat most of the sw ecossytem's margins would shrink (as they should).

Ironically enough the only moat left would be what you can buy from Washington.

seiwj• 2 months ago

Agreed.

We have to wait a whole year (sigh) since firms generally wait a whole financial year to do critical reviews

lenerdenator2• 2 months ago

My concern here is that they'll mix two things:

1) workforce reduction

2) AI spend (reduce tokenmaxing)

They'll expect fewer people to do more with even less, while "more" is continuously increasing.

When I say "more", I mean that the deluge that engineering teams deal with comes from two sources:

1) the business side of companies - marketing, sales, solutions teams, etc.

2) outside actors, mainly security threats

The first source can now move to generate work for engineering faster than ever. They expect the nerds to do what they're told and get the features out now. The more features, the better the product, right? The saving grace here is that they're bound by the same management concerns that engineering has. There's only so much money that they themselves can throw at generating more work for engineering teams, and that might also come under scrutiny from management, so that acts as a brake.

The second source has no such brake, especially not with security threats. Either there's good money to be made by holding company data hostage, or there's an endless supply of resources (read: nation-state resources) dedicated to the effort to attack the company's digital assets. And of course, they're using AI to enable this, just without the "but what about the shareholders!?" handwringing.

If you aren't very, very careful with your token cutting, you're going to put yourself at a disadvantage against that second group.

cdrnsf• 2 months ago

This doesn't account for the fact that review is still a bottleneck, engineers understand much less of the code they're shipping and there'll likely be tech debt they'll have to unwind in the future.

expedition32• 2 months ago

You don't need justification to spend other people's money!

Nobody's going to jail.

heathrow83829• 2 months ago

Didn't google say that AI had increased their company's productivity by 10%? if that's the case, then how can they justify spending 50% to 100% of wages on it?

jimkleiber2• 2 months ago

I wish they would spend some of that on the help/support function within their apps. Whenever I have a problem on Uber, it feels like a never-ending maze to figure out how to get any support, and I consider myself versed in navigating unseemly UI, I can only imagine how much it might frustrate people who struggle navigating apps.

Any idea why their help function seems to impenetrable and if AI might help with it?

redhale2• 2 months ago

I think this is clearly be design. They don't want to provide support, they want you to give up and let your issue go.

jimkleiber2• 2 months ago

It might be. It also lets my loyalty go slowly by slowly. Monopolies work until they collapse.

If you can't tell, it frustrates me so much. I wonder how the internal culture of Uber changed when it went from almost zero interest rates to now trying to make lots of profit.

My friend said he realized Uber can just rely on a steady stream of people either growing up or getting laid off and trying to make a quick buck, so they can treat their drivers poorly as well.

I'm not sure what's happening, just know support may be a lot simpler and cheaper to address than nothing, or at least in the medium to long term, but maybe not?

bmitc• 2 months ago

And here we are.

meerita• 2 months ago

I wonder how hard would be spend maybe 50% of that budget and build a farm of GPUs to run the models locally. I guess it would be a lot of work, but it would be interesting to see how it compares in terms of performance and cost.

gamblor956• 2 months ago

Outside of tech, most companies have already begun pulling back and cancelling their AI spend. (The trend actually started last year.)

Most of the time, the tasks that AI would take over aren't the bottleneck in the business process, so having AI do something faster isn't very useful. It's definitely not useful enough to justify spending more than two digits a month on a recurring subscription, but the price point at which AI is a viable product is far below the price point necessary to sustain even a single AI company.

Uber president says AI spending is getting 'harder to justify'

Related Stories