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Comment by navanchauhan

19 days ago

I think corporate incentives vs personal incentives are slightly different here. As a company trying to experiment in this moment, you should be betting on token cost not being the bottleneck. If the tooling proves valuable, $1k/day per engineer is actually pretty cheap.

At home on my personal setup, I haven't even had to move past the cheapest codex/claude code subscription because it fulfills my needs ¯\_(ツ)_/¯. You can also get a lot of mileage out of the higher tiers of these subscriptions before you need to start paying the APIs directly.

How is 1k/day cheap? Even for a large company?

Takes like this are just baffling to me.

For one engineer that is ~260k a year.

  • In big companies there is always waste, it's just not possible to be super efficient when you have tens of thousands of people. It's one thing in a steady state, low-competition business where you can refine and optimize processes so everyone knows exactly what their job is, but that is generally not the environment that software companies operate in. They need to be able innovate and stay competitive, never moreso than today.

    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.

  • The math is a bit off.

    One day amounts to 24 hours.

    Assuming no overtime, one day translates into 3x 8 hour shifts, or 3x engineers. Suddenly, $260k a year buys 3x engineers.

    Now, assuming that the dark factory stuff can actually work as conjectured, it will work 24x7, 365 days a year, it does not require annual leave, sick leave, observance of public holidays etc. So $365k (adjusted for 24x7, 365) works out to be a cheap deal.

  • I do not really agree with the below, but the logic is probably:

    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.

    • Is the time it takes for an engineer to implement PRs the bottleneck in generating revenue for a software product?

      In my experience it takes humans to know what to build to generate revenue, and most of the time building that product is not spent coding at all. Coding is like the last step. Spending $1k/day in tokens only makes sense if you know exactly what to build already to generate this revenue. Otherwise you are building what exactly? Is the LLM also doing the job of the business side of the house to decide what to build?

    • Right, I understand of course that AI usage and token costs are an investment (probably even a very good one!).

      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.

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  • I assumed that they are saying that you spend $1k per day and that makes the developer as productive as some multiple of the number of people you could hire for that $1k.