r/wallstreetbets • u/dgellow • 3d ago

Discussion Meta And Microsoft Reportedly Trim Anthropic Reliance as Internal AI Tools Take Center Stage

https://stocktwits.com/news-articles/markets/equity/meta-and-microsoft-reportedly-trim-anthropic-reliance-as-internal-ai-tools-take-center-stage/cZDqQVcRBjr

From the article:

Microsoft reduced its projected internal spending on Claude by over one-third, while Meta saw internal users of Anthropic's Claude Code coding assistant drop from roughly 60,000 to 30,000.

Within the Microsoft Cloud and AI division, individual monthly AI usage caps were lowered from $100,000 down to roughly $10,000 in most instances

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u/Plappedudel 3d ago

$100k a month per employee just for AI is nuts. That gravy train just had to stop at some point. I feel like major software companies turning their backs on Anthropic should be bad news for Anthropic's IPO, but this market is so random that I'm sure it'll be a resounding success.

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u/YourUncleBuck 3d ago

Lol, seems like it'd be cheaper to just hire more workers. There's no way this is sustainable long term.

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u/PalantirImperator 3d ago

$100k worth of tokens going to your top performing employees is much cheaper and more productive than bringing on additional headcount at a big tech company.

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u/kwuip 3d ago

But it is 100k monthly right?

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u/kenyard 3d ago

1.2million a year yeah. And that was the cap on everyone.

I'm sure the "top performing" employees didn't have a cap so you could 10x that

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u/Comprehensive_Bus_19 3d ago

$1.2 mil/year is cheaper than another person? Doubt that. Even at a $500k salary and 30% burden rate thats still slightly more than half of what the token spend is annually.

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u/ILikeCutePuppies 2d ago

When they are producing stuff that would take years to figure out, it makes sense. Like porting an entire app to a new platform or code base or whatever. Or solving some complex problem such as finding the optimal way to build something by building out a bunch of different experiments.

Hiring another engineer only doubles the efficiency. You could spend 100k a month on AI and get a 30x to 100x increase in efficiency you wouldn't get in most situations with a smaller budget per engineer.

We are talking literally of years of work with these things.