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Ask HN: Company is rapidly cutting AI tool spend how to prep team?

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Re: Ask HN: Company is rapidly cutting AI tool spend how to prep team?

#12

Post by Sasha_2040 »

With Anthropic's prices it soon will be cheper to hire real people then "hire" their models. If you use it for codding I'm pretty sure you will not be able to find any model which can be hosted on local machine and produce more or less acceptable results. Options - use something more cheaper, Deepseek for example, or if company big enough think about hosting some open source on you private DC with GPUs, I know that some companies develop their own solutions, but I don't have good enough expirience to tell how mach it may cost

Re: Ask HN: Company is rapidly cutting AI tool spend how to prep team?

#14

Post by kasey_junk »

I’d look for a job, not because AI is so important for development that you have to have it, but because your company doesn’t have enough revenue opportunities (or the leadership to find them) that employee productivity doesn’t matter to them.

Companies doing well and growing pass on crazy revenue opportunities because the ones they are focused on are even higher roi. They don’t get bogged down in incremental costs.

If they are cost cutting on dev tooling some bright boss is going to realize the real savings is in cutting down on devs. If you are an American dev team your health insurance costs smoke any amount of token spend.

Re: Ask HN: Company is rapidly cutting AI tool spend how to prep team?

#18

Post by kingkongjaffa »

wtf have you guys been doing. Get on a fixed team plan ASAP instead of paying per token via API pricing.

https://claude.com/pricing#team-&-enterprise

Standard seat All Claude features, plus more usage than Pro* $20 Per seat / month if billed annually. $25 if billed monthly.

Premium seat $100/month

5x more usage than standard seats*

Re: Ask HN: Company is rapidly cutting AI tool spend how to prep team?

#19

Post by baigy »

Snakes3727 wrote: post #6
baigy wrote: post #3

Specifically: to explore your opensource options with compute limitations, ask the community at r/LocalLLaMA on reddit. That's where the current SOTA opensource text-to-text models live.

Yeah i was looking there earlier, its just we thankfully mostly have macbooks, but i recently found out new devs are getting the smaller 8gb ram macbooks as well. Which is going to be even more frusturating. Since my team is mostly remote running LLM on a cluster in the office is not really viable short term.

Hey man, give this a shot: https://github.com/Doorman11991/smallcode

Harnesses such as this - combined with locally hosted AI models - are the future.

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