Earlier quoted context omitted.
Where is level 2?
It’s probably unary interpreted as binary, hence there is no level 2. Level 3 is followed by level 7. Level n is followed by level 2 n + 1. Exponential growth. The singularity is near.
So good...
Uber torches 2026 AI budget on Claude Code in four months
351–360 of 498 posts
Re: Uber torches 2026 AI budget on Claude Code in four months
#352Re: Uber torches 2026 AI budget on Claude Code in four months
#353Honest question, does Uber need that much R&D? And do they expect the ROI to be positive?
Imagine making your product compliant across 100+ countries while regulatiions, labor-laws, tax rules, insurance requirements, and data privacy laws keep changing.
Imagine itegrating dozens of payment methods - many of them highly localized - across emerging and developed markets, while dealing with fraud, chargebacks, KYC, AML, and settlement complexities.
Imagine processing trillions of data points every day - rides, location updates, pricing signals, ETAs, traffic conditions, demand forecasts, payments, support events.... storing it efficiently, querying it in near real time, generating reports, and keeping the whole pipeline reliable. I have woorked in data engineering, and can tell you confidently that this alone requires an enormous R&d budget.
Then there are the apps - not just customer-facing, but driver-facing, courier-facing, merchant-facing, fleet-management, onboarding, support, operations, compliance, finance, and hundreds of internal tools and dashboards.
Then come the integrations. Companies running at Uber's scale genemrally have hundreds of tjese - mapping providers, payment processors, banks, identity verification, tax systems, telecoms, customer support platforms, fraud detection, analytics, ERP, CRM, and more.
... And then there are even more...
Real-time routing and dispatch optimization
Dynamic pricing and marketplace balancing
Fraud detection and account security
Driver/rider safety systems
ML models for ETA, demand forecasting, incentives, and churn prevention
Experimentation infrastructure for thousands of A/B tests
Reliability engineering across globally distributed systems
Data centers / cloud optimization at massive scale
Localization across languages, currencies, addresses, and cultural norms
Customer support automation at global scale
Autonomous vehicle research, mapping, and computer vision
... to be fair, this is all what I could thing of based on my own work experience in related fields... there is definitely as many more systems in reality as mentioned abpve.
Re: Uber torches 2026 AI budget on Claude Code in four months
#354I use a cli tool to build a document of all relevant code and then use ChatGPT 5.5 pro to plan a feature and generate an implementation plan, and then review and edit and paste it into codex on high to implement.
And it works because it won’t stop until the rust compiles. But the code is garbage and makes bad decisions that no junior would. Unmaintainable junk and sometimes I spend more time refactoring than if I would of just built it myself.
People here talking about generating 100ks LoC a month and I’m wondering if it’s a skill issue with me, or Codex or if I should pull all my investments out of companies heavily invested in AI like uber.
Re: Uber torches 2026 AI budget on Claude Code in four months
#355I 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 genuinely challenge someone spending $5-$10k a month to demonstrate how that turns into $50-$100k in value
At a lot of businesses $5-10k/mo of AI spend doesnt even translate into $5-10k/mo value. Churning out code was rarely the business value bottleneck. It was convenient for everybody else to blame developers not writing code fast enough for their failures. Now they have no excuse but I doubt will own up.
Re: Uber torches 2026 AI budget on Claude Code in four months
#356They could have bought all their engines their own massive GPU. They could have built out their own DC. Nuts...
Re: Uber torches 2026 AI budget on Claude Code in four months
#357Earlier quoted context omitted.
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…
> But the reality is that with Claude, I can get the work done in 1 day that would take me 5 days of struggling, Is it really a 5x ROI? Where are all the apps, games, platforms, SAAS's, feature s that have been backlogged for 5 years that are all of a sudden getting done? Because I see a modest ROI, and an _awful lot_ of shovelware.
> I'm new to my team and the codebase isn't huge, but it's large enough that there are plenty of parts I have little understanding about.
When you're new to the codebase, things that take an experienced colleague one day to do can take a newbie 3-5 days to do.
Re: Uber torches 2026 AI budget on Claude Code in four months
#358This Claudemaxxing phenomenon is amusing as hell.
I've been able to get by with the $20pm Pro subscription and reap great value out of Claude Code.
I feel like it really is about:
- Don't feed it the works of Shakespeare into the context window if all it's working on is a few files. I actually don't have a Claude.md file in my projects.
- I write the prompt as if I was giving instructions to another developer or to myself on how I want to approach a specific coding, with a numbered step plan. I've actually been able to take the details written into a Jira ticket on a work project, feed it into Clade Code, and get really good results from it.
- If you are responsible for the output, then you need to review the output - that does put a natural constraint on the tool's usage, but ultimately it is you who uses the tool, not the other way around.
I feel like that's the thing - you have to find the right cadence, just like with running or driving a car - you need to find the level at which you control the car, at which you maintain a consistent pace, and at which you get code that does what you need it to do and meets the quality threshold you want.
Re: Uber torches 2026 AI budget on Claude Code in four months
#359This doesn’t work at all
Re: Uber torches 2026 AI budget on Claude Code in four months
#360I 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
But what do they actually do?
I keep seeing people wax poetic about the mountains and mountains of code that LLMs are dumping out but I'm yet to anywhere near a proportionate amount of actually useful new apps or features. And if anything the useful ones I do find are just more shovels for more AI. When do we get to the part where we start seeing the 10x gains from the billions of lines of code that have probably been generated at this point?