"The leaderboard, which ranked employees and teams by token consumption, inadvertently incentivized usage volume over productive output." Who could possibly have predicted that happening?
I still don't understand how Mark Zuckerberg has any serious investors, he went on this AI tangent and has absolutely nothing to show for it, despite FB / Meta having built some key tech in the space. He needs to stop trying to do something "different" and literally try and build a serious coding agent he can sell, he could have probably had something worthwhile in that space by now. He started being drastically more…
Meta caps internal AI token spending
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Re: Meta caps internal AI token spending
#102"The leaderboard, which ranked employees and teams by token consumption, inadvertently incentivized usage volume over productive output." Who could possibly have predicted that happening?
It’s funny how many times the same thing happens at each large company. I think people’s thought process is this: > Oh wow! If I paid for this myself I would have spent a lot of money! Are other people spending as much as me? I’m going to create a leaderboard! > Oh no, my misinformed manager is using the leaderboard as a slight of hand for work. I need to game this now. Then the leaderboard is banned… I can’t see how…
Re: Meta caps internal AI token spending
#103I’d be curious to see the breakdown on spending by use case. I’ve heard it said that the majority of tokenmaxing comes from none technical uses like reading PDFs, creating PowerPoints, generating graphics/images… ect. But I’ve never heard any actual proof to that.
Re: Meta caps internal AI token spending
#104I’d be curious to see the breakdown on spending by use case. I’ve heard it said that the majority of tokenmaxing comes from none technical uses like reading PDFs, creating PowerPoints, generating graphics/images… ect. But I’ve never heard any actual proof to that.
One thing I find fascinating as a software engineer who talks to non software engineers who use AI tools is how "reading PDFs" is not more of a solved problem. What I mean is that uploading a PDF into a chatbot tool seems to be an extraordinarily obvious use case that non technical (and technical) users would want to do. IMO claude, chatgpt/codex, etc should be able to optimize the PDF use case to be extremely token…
Re: Meta caps internal AI token spending
#105Earlier quoted context omitted.
It’s funny how many times the same thing happens at each large company. I think people’s thought process is this: > Oh wow! If I paid for this myself I would have spent a lot of money! Are other people spending as much as me? I’m going to create a leaderboard! > Oh no, my misinformed manager is using the leaderboard as a slight of hand for work. I need to game this now. Then the leaderboard is banned… I can’t see how…
There is zero chance that this is how the leaderboards came to be.
Re: Meta caps internal AI token spending
#106Earlier quoted context omitted.
measuring uptime? I've seen Anthropic's status page, and they are a >$1 Trillion dollar company who "largely solved" coding. so clearly you aren't correct. /s
Ok, uptime. How do you measure an individual’s contribution to uptime? If Claude goes down does everyone take a hit? If Claude stays up everyone gets rewarded? If so, your metric cannot distinguish between a bad engineer and a good one. If not, you have the same problem you started with: measuring contributions to “uptime”.
A metric that moves in the same direction and amount for everyone based on external event isn’t a problem. The delta in performance of the great engineer will outweigh that of the poor, since the metric movement that is due to external circumstances will be the same in each kind of engineer and thus not count.
Re: Meta caps internal AI token spending
#107Within a few weeks of telling people at our company that if they don’t use AI they will be replaced by someone who does, they just announced that their allocation with ChatGPT has reset and are now panicking as they blew through their million token allocation for this month in under six hours - you can’t make this shit up.
Re: Meta caps internal AI token spending
#108measure outcomes (impact), not effort (token usage, lines of code, code coverage, hours worked, etc.)
> measure outcomes (impact) This is also not easy. In particular proactively preventing bugs is not rewarded
The main way I think you can proactively prevent bugs in a meaningful way is by crafting and propagating better architecture.
Better (or worse) architecture and adoption of it can be measured through a mix of quantitative and qualitative means so those metrics could be used to evaluate the impact of the engineer driving that architecture.
Re: Meta caps internal AI token spending
#109Earlier quoted context omitted.
One thing I find fascinating as a software engineer who talks to non software engineers who use AI tools is how "reading PDFs" is not more of a solved problem. What I mean is that uploading a PDF into a chatbot tool seems to be an extraordinarily obvious use case that non technical (and technical) users would want to do. IMO claude, chatgpt/codex, etc should be able to optimize the PDF use case to be extremely token…
Because PDFs are a nightmare of a format and the only thing that’s is reasonably guaranteed about them is they will render to an image that people can read, the parsing of which will be much less token efficient than the equivalent text
Re: Meta caps internal AI token spending
#110Various discussions:
Meta’s chaotic AI strategy
https://news.ycombinator.com/item?id=48523271
Companies rein in AI usage as costs strain budgets
https://news.ycombinator.com/item?id=48602571
Meta CTO Andrew Bosworth Admits the Company's AI Reorg Was 'Atrocious'
https://news.ycombinator.com/item?id=48548461
Tokenmaxxing is dead, long live tokenmaxxing