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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

#371
post #295

Earlier quoted context omitted.

If Uber is like most other companies, there's a leaderboard for AI tokens consumed. If maximizing your token usage is going to get you to the top of the leaderboard, and therefore promoted for "productivity", people are going to find creative ways to be "productive".

The tokenmaxxing leaderboard where I work has a lot of new hires on it

Asking the LLM to spawn a subagent per file and look for bugs is a good way to waste a lot of tokens real fast for leaderboard success, and it's pretty defensible as useful work if someone tries to call you on it.

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

#372
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…

1. Worktrees

2. Multiple simultaneous projects

3. Orchestration that includes handling of CI workflow

4. Active work to further improve or refine tooling

5. Experimentation producing muscle memory as experience versus code output

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

#373
post #371

Earlier quoted context omitted.

The tokenmaxxing leaderboard where I work has a lot of new hires on it

Asking the LLM to spawn a subagent per file and look for bugs is a good way to waste a lot of tokens real fast for leaderboard success, and it's pretty defensible as useful work if someone tries to call you on it.

Yeah and it's a natural extension of the typical busywork people used to spam pre-AI, "I split your ticket into 10 tickets and made a kanban for it"

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

#374
Relevant Pragmatic Engineer newsletter with many more cases along these lines, along with how some people are handling them: https://newsletter.pragmaticengineer.com/p/the-pulse-token-s...

Tokenmaxxing seems more and more like a way to encourage experimentation and learning, and incidents like this are a part of learning. Like, today devs simply use the most expensive model by default, even to do extremely simple things. This is obviously wasteful and costly, and budgets will soon be imposed, but this is how they're figuring out the economics.

For instance, like we estimate story points, we may estimate token budgets. At that point, why waste time and money invoking a model for a simple refactor when you could do it with a few keystrokes in an IDE? And why use a frontier model when an open-source local model could spit out that throwaway script? Local models can be tokenmaxxed, but frontier models will still be needed and will be used judiciously. Those are essentially trade-offs, and will eventually be empirically driven, which is what engineering is largely about.

So economics will soon push engineers back to do what they're paid to do: engineering. Just that it will look very different compared to what we're used to.

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

#375

Earlier quoted context omitted.

What if you're the SRE and the code fixes mean the site goes from 99% uptime to 99.9% up? How do you measure the revenue from that?

Depending if the site has a direct competitor and non-sticky customers, you can often get accurate loss estimates from outages. For example, friends of mine at Doordash would know when UberEats was down by the corresponding spike in traffic to their app. The competitor captures all the lost traffic. Most enterprises will have a harder time quantifying losses, as some percentage of customers will come back later. To u…

Seems like an unscrupulous operator would take action to take down their competitor's site with a DDoS in order to drive business to themselves.

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

#376
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 what you're paying them. If it takes them a day to bring costs down by $1 an invocation, then it takes almost 2 years to recoup the salary costs. It's worse because LLMs currently change so much I wouldn't be confident that their solution won't be broken before the 2 year period. Will we still be tool calling in 2 years, or will that be something new? Will thinking still be a thing, or will it be superceded by something else? I don't think anyone knows, even the frontier providers.

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

#377
post #175
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 have ancedotal examples of claude code choosing a solution to a problem that is ridiculously token inefficient. One example - was giving several agents different sub problems to solve in a complex ML / forecasting problem. Each agent would write + run + read a jupyter notebook. This worked ok, the notebooks would be verbose but it was fine... until one of them wrote out hundreds of thousands of rows to a cell outpu…

> have claude read all your emails every day...

To be fair, I do that. 2-3 times a day, in fact. Not all of my emails (the archive has ballooned to several hundred thousand messages total), but the most recent ones certainly.

My standard prompt is along the lines of "go through the last N days of my emails, identify all threads that I need to know about, action on or follow up with". N is usually a number between 2 and 5. I've specified a standing of set of rules to easily know what is likely a source of noise to aid in skipping the bot spam.

The company is charged API pricing through an enterprise contract, and I remain persistently curious how much I burn. My daily admin-related token expenses appear to fluctuate between $1 and $5. For something that saves me up to 2h of time a day I consider that a rather tolerable deal. (When I dive in to code to do refactors or deep investigations, I can spend as much as $25 a day.)

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

#378
post #300
post #285

Earlier quoted context omitted.

I can't even tell whether this comment is serious or not.

https://www.businessinsider.com/jensen-huang-500k-engineers-...

Person who profits indirectly from AI token spend advocates AI token spend.

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

#379
post #64
post #57

Earlier quoted context omitted.

That's my take as well. I've had my unPRed branches grabbed up and blindly merged by an agent twice now. The guy doing it was shocked both times that his PR had my change sets in it. Also one engineer is treating the code as assembly. I've asked some pointed questions about code in his PR and the response was "yeah, I don't know that's what the agent did". Edit: To everyone freaking out about the second guy. Yeah, I…

To that last guy, as the manager I would say "What is it that you do here??"

I then just basically space out for a while.

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

#380
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.

Actually no. We ask business analysts to supply documentation for whole products. We use AI to analyze that documentation and after that we use AI to create tasks in Jira. Business analysts will review them.

After that we use AI to translate the tasks to a more technical view.

After that we use AI to implement the tasks.

After that we use AI to review the tasks.

After that a human QA tests the tasks.

If all is good, the code is merged and lands in production.

And yes, we burn a lot of tokens but the process is very fast. It takes months instead of years.

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