I find it useful that if they cut the use altogether I will pay for it out of pocket.

dghlsakjg 2 hours ago | parent | next [-]

Would you decide its usefulness based on how high the bill is, or how many things you get done while using it?

The former is the issue, and how many companies have been operating. It's like a trucking company ranking driver effectiveness by fuel used instead of by cargo moved.

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sottol 3 hours ago | parent | prev | next [-]

Maybe that's the plan :)

But on a more serious note, do we know how much Uber spent per technical employee/month? I assume it is far more than even any of those $200 "max ai" plans.

And the other question is how much the public would be willing to spend, in my estimation this is as "cheap" as it will ever get (main-stream at least).

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KronisLV 3 hours ago | parent | next [-]

> I assume it is far more than even any of those $200 "max ai" plans.

Am in a random small company, colleague spent 100 EUR a day on Sonnet through AWS Bedrock (needed to use a EU region). Paying for tokens will get you in a deep hole financially compared to any of the subscriptions, unless it's like DeepSeek or one of the other models that are priced a bit better, though that's also a tradeoff in what they can/cannot do and also where the data goes. Ended up trying out the Mistral subscription for the US stuff btw, it was fine.

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Marciplan 3 hours ago | parent | prev [-]

bigCo’s don’t get to do the $200 Max plans, they have unlimited plans but get charged like API

	▲	sottol 2 hours ago \| parent [-]
		Exactly. But I did find an article ([1]) and spend doesn't seem that high per engineer ($150 to $250 per eng) - at least on average, I assume the costs were skyrocketing towards the end. > Adoption climbed from 32 percent of engineers in February to 84 percent classified as agentic coding users by March. By spring, 95 percent of Uber engineers used artificial intelligence tools monthly, and roughly 70 percent of committed code originated from those tools. About 11 percent of live backend updates were written by agents with no human in the loop, according to Uber's own disclosures. > The numbers behind the spend are what make the story instructive rather than anecdotal. Monthly cost per engineer ranged from $150 to $250 on average, with power users running between $500 and $2,000. My guess is that the reason to rethink AI-spend was probably the exponential growth in cost over time, and tokenmaxxing payoff not being immediately obvious as mentioned in the article. [1] https://www.forbes.com/sites/janakirammsv/2026/05/17/uber-bu...

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mattlondon 2 hours ago | parent | prev | next [-]

Probably long term each dev gets their own GPU and runs a model locally I expect. Seems like a more sustainable approach, even if a local model is not absolute SOTA.

	▲	ianm218 an hour ago \| parent [-]
		GPUs are much more efficient at parallelizing requests for LLMs so it's going to much more efficient to centrally host. Maybe big companies it would make sense to get their own though.

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iwontberude 3 hours ago | parent | prev | next [-]

Except you won’t because they will threaten to fire you and force you to route all of your AI through data protection proxy to stop exfiltration by filtering and tracking prompts/response tokens.

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throwaway613746 2 hours ago | parent | prev [-]

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