Takes like this are just baffling to me.
For one engineer that is ~260k a year.
The thing with AI is that it ranges from net-negative to easily brute forcing tedious things that we never have considered wasting human time on. We can't figure out where the leverage is unless all the subject matter experts in their various organizational niches really check their assumptions and get creative about experimenting and just trying different things that may never have crossed their mind before. Obviously over time best practices will emerge and get socialized, but with the rate that AI has been improving lately, it makes a lot of sense to just give employees carte blanche to explore. Soon enough there will be more scrutiny and optimization, but that doesn't really make sense without a better understanding of what is possible.
1) Engineering investment at companies generally pays off in multiples of what is spent on engineering time. Say you pay 10 engineers $200k / year each and the features those 10 engineers build grow yearly revenue by $10M. That’s a 4x ROI and clearly a good deal. (Of course, this only applies up to some ceiling; not every company has enough TAM to grow as big as Amazon).
2) Giving engineers near-unlimited access to token usage means they can create even more features, in a way that still produces positive ROI per token. This is the part I disagree with most. It’s complicated. You cannot just ship infinite slop and make money. It glosses over massive complexity in how software is delivered and used.
3) Therefore (so the argument goes) you should not cap tokens and should encourage engineers to use as many as possible.
Like I said, I don’t agree with this argument. But the key thing here is step 1. Engineering time is an investment to grow revenue. If you really could get positive ROI per token in revenue growth, you should buy infinite tokens until you hit the ceiling of your business.
Of course, the real world does not work like this.
But my point is moreso that saying 1k a day is cheap is ridiculous. Even for a company that expects an ROI on that investment. There’s risks involved and as you said, diminishing returns on software output.
I find AI bros view of the economics of AI usage strange. It’s reasonable to me to say you think its a good investment, but to say it’s cheap is a whole different thing.
The best you can say is “high cost but positive ROI investment.” Although I don’t think that’s true beyond a certain point either, certainly not outside special cases like small startups with a lot of funding trying to build a product quickly. You can’t just spew tokens about and expect revenue to increase.
That said, I do reserve some special scorn for companies that penny-pinch on AI tooling. Any CTO or CEO who thinks a $200/month Claude Max subscription (or equivalent) for each developer is too much money to spent really needs to rethink their whole model of software ROI and costs. You’re often paying your devs >$100k yr and you won’t pay $2k / yr to make them more productive? I understand there are budget and planning cycle constraints blah blah, but… really?!