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

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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The biggest blunder, so far, is the $1.8-million bill that came from a failed Claude Sonnet AI deployment, which was supposed to match author details with listings on Amazon, representing an 860% increase over the allocated budget that was only detected some five months after the issue started happening. Other problems that surfaced include a $541,000 additional cost that came from a project building, ironically, a financial auditing tool, and a $134,000 extra expense for a system designed to reduce delivery times in the company’s logistics network.

“As with any new technology, we’re experimenting, learning and improving how we use it, including how we drive cost efficiencies,” Amazon said in an internal presentation, according to FT. “Cherry-picking small, isolated examples where teams are learning from one another and portraying them as business as usual doesn’t reflect how teams across Amazon are using AI.” And even though overspending more than a million dollars on failed AI projects might seem excessive for the average person, the tech giant’s latest quarterly revenue sits at more than $181 billion, meaning these excess AI expenses don’t even account for 0.1% of what it makes in a month.

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This is not the first time that AI-related issues have cropped up in Amazon’s workflow. Earlier this year, AWS reported several outages that were driven by AI coding bot blunders, but the company fixed this by limiting the access of AI agents instead of giving them the same permissions as the senior engineers that they’re tied to. It also used to have an internal leaderboard that showed which employees used AI the most, but has since dropped it as spiraling AI costs made them think twice about the policy.

Many tech companies have been pushing their people to use AI, supposedly to increase productivity through tokenmaxxing. However, the Uber CTO said that there is no link between this policy and shipping successful products. And as agents took over and AI providers switched from subscription to per-token models, costs have become so great that companies are using up their annual budgets in a matter of weeks. While this might not be an immediate issue for tech giants like Amazon and Microsoft, it is unsustainable for most other companies out there.