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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

#201

Post by hyperpape »

dijit wrote: post #78
hyperpape wrote: post #59

I love how these articles drop, and all of a sudden HN is filled with people who think engineering productivity is simple to measure. Yes, productivity implies revenue (or cost reduction), and revenue is measurable. However: 1. You spend money today to build features that drive revenue in the future, so when expenses go up rapidly today, you don’t yet have the revenue to measure. 2. It’s inherently a counterfactual c…

> HN is filled with people who think engineering productivity is simple to measure. I think the prevailing (correct) consensus is that developer productivity is actually very hard to measure, and every time it is attempted the measure is immediately made a target making the whole thing pointless even if it had been a solid measurement- which it wasn't. IDK where you're getting the idea here that measuring productivit…

I do not think it is easy, like I said. I am saying other people are acting like it’s easy.

See the second comment on this article. https://news.ycombinator.com/item?id=47976781

See @emp17344 responding to me.

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

#202

Post by gedy »

Aurornis wrote: post #127
quaintdev wrote: post #105

Earlier quoted context omitted.

Begs the question if we should move on to minimal microservices so that whole project lives in context of llm. I hardly have to do anything when I'm working with small project with llm.

In my experience, the result is just more crawling across the separate microservices and additional reasoning to confirm how it all fits together. The monolithic codebases are easier to crawl for any problem that can't be conveniently isolated to a single microservice.

Sounds like tight coupling issue, not services per se

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

#203

Post by leptons »

internetter wrote: post #6

I know I'm responding to AI right now, but > which means figuring out if the company can afford this level of productivity at scale. If it was actually productive, then the revenue would increase and affordability wouldn't be a question.

That is not true at all. No matter how "productive" a company is means nothing if people aren't buying your product. And using LLMs to be more productive will not convince anyone to buy your product. Human creativity and intuition to make a product that people want to use is what sells. Productivity for productivity's sake doesn't really move the needle at all, and can make things worse.

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

#204

Post by kurige »

BeetleB wrote: post #170
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…

First: There's the obvious "If the company is letting me do it, I'll be wasteful." This includes not clearing/compacting the context often. Opus now has a 1M context window, and quality is good to at least 200K. So each query is burning a lot of tokens until you clear/compact. People have already mentioned the size/complexity of the codebase. I'm new to my team and the codebase isn't huge, but it's large enough that…

> This includes not clearing/compacting the context often. Opus now has a 1M context window, and quality is good to at least 200K. So each query is burning a lot of tokens until you clear/compact.

I see this repeated by others, including coworkers. It completely ignores caching. Caching itself is complicated, but the "longer context window = more expensive" is not 100% true and you are hampering yourself if you're not taking full advantage of large context windows.

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

#206

Post by drfloyd51 »

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…

Your estimates do not account for speed of delivery. If an AI can deliver 10x faster, the target is less than 10x a dev salary.

But 10x faster also gets you to market sooner. Which has value.

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

#207

Post by ModernMech »

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…

I dunno I've seen agents make boneheaded mistakes even a junior engineer wouldn't make. Treating them as strictly better than junior engineers is a problem, not just for that reason but because you're effectively killing the pipline for senior engineers. Then what?

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

#208

Post by Raed667 »

zeafoamrun wrote: post #190
trjordan wrote: post #125

> figuring out if the company can afford this level of productivity at scale This is the thing that boggles my mind. They spent their budget. They have 4 months of data. What do they have to show for it? I'm not a hater; I'm not a luddite. I have a $200 Max plan and I use it. But are you saying that Uber made this tool available, urged everybody to use it, and is confused about what happens when it worked? It's one t…

The personal max and teams plan actually are an amazing bargain compared to the API PAYG cost you get with Enterprise. I guess they really need their Enterprise features though, otherwise they could just tell users to expense a $200 max sub. Enterprises gonna Enterprise.

Entreprise gets you the written agreement that the data you send to Claude will never be used for model training

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

#209

Post by soleveloper »

entropicdrifter wrote: post #24
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'm on the same page. Do people not analyze the problems themselves? Are they just copy/pasting their entire ticket description into Claude Code and having it iterate until they land on something that works? I don't get it.

> Are they just copy/pasting their entire ticket description into Claude Code and having it iterate until they land on something that works?

"Their ticket" = that was AI generated. After which they will wait their AI generated PR be checked by an automated AI QA that will validate against the AI generated spec.

It feels like important metric of "corporate AI adoption" should be how effective the human in steering the AI.

IF THE HUMAN ISN'T EFFECTIVE, THE HUMAN NEEDS TO GO.

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

#210

Post by mkehrt »

solenoid0937 wrote: post #148
ravenstine wrote: post #71

Earlier quoted context omitted.

And why wouldn't they? Companies are quite literally instructing them to do so. I work at such a company and have heard similar anecdotes from colleagues that work at other companies.

Why wouldn't you do this even if not instructed to do so? I can do so much more with my spare time now. I throw agents at problems and get way more done. $1k in tokens every day is easy to hit.

What exactly are you “getting done”? I’m really curious what you’re doing with so many tokens.
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