Amazon accidentally spent $1.8 million using Claude for menial coding task, went 860% over budget — 'catastrophically expensive' coding blunders discovered in internal Amazon AI usage metrics

AI robot agents
(Image credit: Getty Images)

Amazon has several internal reports that show how AI is causing the company to overspend on various projects. The Financial Times reports that the cost overruns reached $1.8 million, and that is just for one project. These mistakes used to be “trivially cheap,” but AI models made them “catastrophically expensive,” especially as token spending drastically increased with the deployment of AI agents.

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Jowi Morales
Contributing Writer

Jowi Morales is a tech enthusiast with years of experience working in the industry. He’s been writing with several tech publications since 2021, where he’s been interested in tech hardware and consumer electronics.

  • warezme
    Illustrates how multi-million dollar AI over spending is trivial to multibillion dollar corporations but wage increases for human resources is just to much.
    Reply
  • -Fran-
    In more and more "AI" meetings, I've been trying to teach people that local models exist and, while not as "good" (quotes intentional), they're actually a great trade off, even for corpo usage when you have the processing spare capacity and it seems like I'm getting somewhere, which is nice.

    This being said, until they don't try to reclaim the "compute" in some way, these stupid things will keep happening for any company that wants to explore AI in any capacity.

    Heck, even small companies can get really good local models running pretty much anywhere for cheap and get started with hybrid models.

    Regards.
    Reply
  • oofdragon
    180billion and they can't raise peoples salary... wouldn't ever work for, work with or buy services from a business like this
    Reply
  • Zaranthos
    I did chuckle when I read this, not gonna lie. At least I'm not the only one sacrificing to train AI. I really love it when it works, but when it doesn't it's some of the most convincing fail I've ever seen. I can't reclaim that time but I can hope it helps make the next generation AI models better. Thankfully the very worst of AI is usually in the gaming space when you're asking it about strategy, builds, or general game hints. Since it scraped data from Reddit, forums, and every corner of the internet it is full of 12 year old kids wisdom on beta versions of games now 10 years old and the AI has to be "trained" to use a little more common sense before creating the most convincing re-write of the source garbage.
    Reply
  • alan.campbell99
    Not sure they can get better if you cannot eliminate the possibility of hallucinations which is inherent to LLMs. I suppose it's manageable on an individual level when you're already versed in the subject matter you're working with and can spot the inevitable mistakes, not so with anyone not versed. Some things like financials you probably shouldn't be messing around with when you need accuracy.
    With respect to Amazon I personally resist using them for anything, among other reasons being their treatment of fulfillment center workers. I wouldn't shed any tears for the company wasting money except that these low level employees will more likely be affected than the c-suite business idiots.
    Reply
  • King_V
    Why does it take the CTO of a toxic company to be the one to say that there's no link between tokenmaxxing and greater productivity?
    Reply
  • JRStern
    warezme said:
    Illustrates how multi-million dollar AI over spending is trivial to multibillion dollar corporations but wage increases for human resources is just to much.
    exactamundo
    Reply
  • JRStern
    This is entirely implicit in the basic setup.
    You tell the AI, "hey, fix that semicolon!"
    $50,000 later it says, "OK, done."
    It takes $49,999 to input the model and $1 to do the work.
    How often have I done that with compilers? Zillions of times. At virtually zero cost.
    Reply
  • derekullo
    alan.campbell99 said:
    Not sure they can get better if you cannot eliminate the possibility of hallucinations which is inherent to LLMs. I suppose it's manageable on an individual level when you're already versed in the subject matter you're working with and can spot the inevitable mistakes, not so with anyone not versed. Some things like financials you probably shouldn't be messing around with when you need accuracy.
    With respect to Amazon I personally resist using them for anything, among other reasons being their treatment of fulfillment center workers. I wouldn't shed any tears for the company wasting money except that these low level employees will more likely be affected than the c-suite business idiots.
    Just because I'm not 100% accurate with a hammer .... doesn't mean I refuse to use a hammer!
    Reply