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Uber torches 2026 AI budget on Claude Code in four months

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Re: Uber torches 2026 AI budget on Claude Code in four months

#381

Post by DeathArrow »

DeathArrow wrote: post #178
abuani wrote: post #17

I take a peak every month or so at spend for my company and notice more and more are consumed $1k in tokens a month and it is bewildering to me how. I use llms daily, and see anywhere from $200-$400 tops. This is using the most expensive models, in deep thinking mode. So I'm not a Luddite against the usage of them. I just can't figure how _how_ to burn that much money a month responsibly. I genuinely challenge someon…

It really depends on the way you use AI. If you just prompt it for a task and either accept or reject the output, you won't spend much. But if you are like me, you aggressively document and brainstorm before planning, you review that documentation with subagents, make modifications, you aggressively plan, you verify that plan with subagents,make modifications, have a large number of phases, planning again for each ph…

And also some of use run tens of rounds of gradually improving the projects. And that burns tokens like crazy.

Re: Uber torches 2026 AI budget on Claude Code in four months

#382

Post by DeathArrow »

in_cahoots wrote: post #364
DeathArrow wrote: post #178

Earlier quoted context omitted.

It really depends on the way you use AI. If you just prompt it for a task and either accept or reject the output, you won't spend much. But if you are like me, you aggressively document and brainstorm before planning, you review that documentation with subagents, make modifications, you aggressively plan, you verify that plan with subagents,make modifications, have a large number of phases, planning again for each ph…

Are you bringing in at least $1.25M in additional yearly revenue to your company?

I think more than that.

Re: Uber torches 2026 AI budget on Claude Code in four months

#383

Post by SpaceNoodled »

Galanwe wrote: post #278
abuani wrote: post #17

I take a peak every month or so at spend for my company and notice more and more are consumed $1k in tokens a month and it is bewildering to me how. I use llms daily, and see anywhere from $200-$400 tops. This is using the most expensive models, in deep thinking mode. So I'm not a Luddite against the usage of them. I just can't figure how _how_ to burn that much money a month responsibly. I genuinely challenge someon…

> I just can't figure how _how_ to burn that much money a month responsibly. From my experience, this happens essentially by three means: - Level 0 (beginner users) long lived conversations: If you dont get in the habit of compressing, or otherwise manually forcing the model to summarize/checkpoint its work, you will often find people perpetually reusing the same conversation. This is especially true for _beginners_,…

What about Level 2?

Re: Uber torches 2026 AI budget on Claude Code in four months

#384

Post by sarchertech »

kansface wrote: post #189
abuani wrote: post #17

I take a peak every month or so at spend for my company and notice more and more are consumed $1k in tokens a month and it is bewildering to me how. I use llms daily, and see anywhere from $200-$400 tops. This is using the most expensive models, in deep thinking mode. So I'm not a Luddite against the usage of them. I just can't figure how _how_ to burn that much money a month responsibly. I genuinely challenge someon…

> I just can't figure how _how_ to burn that much money a month responsibly. I always have a few agents (2-5) doing research and working on plans in parallel. A plan is a thorough and unambiguous document describing the process to implement some feature. It contains goals, non-goals, data models, access patterns, explicit semantics, migrations, phasing, requirements, acceptance criteria, phased and final. Plans often…

> In my highest volume weeks, I ship low hundreds of thousands of lines of software not counting changes to deps.

I suspicious you actually get claude to output that much usable code in a week, but maybe you do.

But I’m 100% positive that you’re not shipping even a small fraction of the amount of value that someone reading this 2 years ago would have expected from hundreds of thousands of lines of code.

Re: Uber torches 2026 AI budget on Claude Code in four months

#385

Post by pyinstallwoes »

laurels-marts wrote: post #369
Galanwe wrote: post #278

Earlier quoted context omitted.

> I just can't figure how _how_ to burn that much money a month responsibly. From my experience, this happens essentially by three means: - Level 0 (beginner users) long lived conversations: If you dont get in the habit of compressing, or otherwise manually forcing the model to summarize/checkpoint its work, you will often find people perpetually reusing the same conversation. This is especially true for _beginners_,…

I’m basically doing lvl 3. There’s not a single port in my local worktree’s .env that’s not guaranteed to be unique across all worktrees. Skills for agent to start their own managed dev server, launch their own isolated instance of chrome etc. literally end-to-end code and debug the entire app. I do have to say though you have to know the app inside out and have to have a pretty well groomed backlog in order to run t…

Would love to learn more on how you do it. The various skills, tasks, workflow. If you have time and can share it. That would be valuable. :)

Re: Uber torches 2026 AI budget on Claude Code in four months

#386

Post by skirmish »

th0raway wrote: post #257
brokencode wrote: post #30

Earlier quoted context omitted.

Really depends on the repo you’re working in. If it’s very large, especially if the tool needs to refer to documentation for a lot of custom frameworks and APIs, you often end up needing very large context windows that burn through tokens faster. If it’s smaller or sticks with common frameworks that the model was trained on, it’s able to do a lot more with smaller context windows and token usage is way lower.

Yes, in a reasonable microservice land where the places you need to connect to are all documented in very concise places, you have have extremely productive $10 days. In the giant monorepo with everything custom, you can't just rely on built in knowledge of 80% of you libraries, so it's a very different world. A place like Google has to be so much better off just training library concepts in, given how much of the th…

> A place like Google has to be so much better off just training library concepts in

They did that, there was a special version of Gemini fine-tuned on internal code. But then the main model moves so fast that it is hard to keep such fine-tunes up to date and on the latest.

Re: Uber torches 2026 AI budget on Claude Code in four months

#387

Post by pretzel5297 »

everforward wrote: post #376
jjcm wrote: post #322

Speaking as someone who's bootstrapping here, I'm often envious of engineers at these larger companies, but I also worry that the incentives are screwed up. If I were an engineer at Uber, why wouldn't I select gpt 5.5 pro @ very high thinking + fast mode for a prompt? There's no incentive not to use the most powerful (and thus most expensive) model for even the smallest of changes. I tried one of these prompts for so…

SWE's are expensive; median salary is $133k (not counting health insurance, payroll taxes, etc). If you can shave off an hour of dev time with $40 in LLM credits, that's $26.50 cheaper than having them do it without. I'm not entirely convinced it works out that way so far, but that's the theory. Trying to bring down LLM costs is sort of a double-edged sword, because the dev needs to be cutting LLM costs by more than…

> If you can shave off an hour of dev time with $40 in LLM credits, that's $26.50 cheaper than having them do it without.

This assumes that that hour shaved was used elsewhere productively which is not the case.

Re: Uber torches 2026 AI budget on Claude Code in four months

#388

Post by jb3689 »

abuani wrote: post #17

I take a peak every month or so at spend for my company and notice more and more are consumed $1k in tokens a month and it is bewildering to me how. I use llms daily, and see anywhere from $200-$400 tops. This is using the most expensive models, in deep thinking mode. So I'm not a Luddite against the usage of them. I just can't figure how _how_ to burn that much money a month responsibly. I genuinely challenge someon…

$400 * 23 business days would be $9k. Sounds ballpark to me

Re: Uber torches 2026 AI budget on Claude Code in four months

#389

Post by scuff3d »

ethin wrote: post #332
scuff3d wrote: post #288

Earlier quoted context omitted.

I agree that you can't draw any conclusions about AI, but their revenue increased by 33% percent. That's just straight income before any taxes or costs are applied.

Yes, but that doesn't mean AI increased their revenue. Is there definitive proof that AI/LLMs caused this increase?

I completely agree with you. I pointed out replying to the same person that in the same report their ad impressions were up 20% and the price per ad was up 12%, which account for a huge amount chunk of that revenue increase.

All I was saying here was that tax breaks wouldn't impact revenue since revenue is reported before taxes, operating costs and anything else.

Re: Uber torches 2026 AI budget on Claude Code in four months

#390

Post by daheza »

risyachka wrote: post #345
Galanwe wrote: post #278

Earlier quoted context omitted.

> I just can't figure how _how_ to burn that much money a month responsibly. From my experience, this happens essentially by three means: - Level 0 (beginner users) long lived conversations: If you dont get in the habit of compressing, or otherwise manually forcing the model to summarize/checkpoint its work, you will often find people perpetually reusing the same conversation. This is especially true for _beginners_,…

>> Again, not necessarily bad in itself, yeah, it is bad. Human brain is not able to properly assess this amount of changes. To understand even a small change you need a lot of capacity. To understand thousands of lines - impossible. This is pure slop pouring into prod and we can see more and more consequences of this in all big corps's products - things start to break more and more exponentially faster.

The thing I keep coming back to is - does it matter?

Really does it matter if a company produces something that breaks constantly or gets worse or slower.(See github) Megacorps have a wide moat and have forced out all competition or they just buy them with low interest loans.

The quality of products keeps getting worse and we can do nothing but live with it. So if that's the state of the world, why wouldn't you just push as many "features" as fast as possible. More is rewarded. Less is punished. Quality does not matter.

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