Yes. It spawned multiple subagents to run different experiments to benchmark a lot of different things, reviewed CI logs from past runs, etc. In the end, there were changes to what/how we cached, various code quality checks, speeding up test runners, and many other things.
The cost of the standard `actions_linux` is $0.006/minute, so spending $500 to save 6m per invocation, break-even is at ~14k invocations. But, if they're using larger machines and/or parallel jobs the $$$ saving accrues faster. IMO the wall-time saving shortening feedback loop may be a bigger win, but harder to value.
Pricing is dropping quick. Inference is so cheap, I think they are losing a lot less money selling subscriptions than you think. It might even be more expensive managing the load, than actually selling the tokens at subscription prices.
We are seeing with OpenAI, allegedly through their new pricing scheme, as intelligence and model efficiency increases they offer the same throughput while advertising 1/2 as much usage, letting Astra consume more usage, essentially only being available to those wealthy enough to afford it while still offering essentially unlimited Sol and Luna to their subscription tiers.
Also if you're cache hit rate is high enough a billion tokens tokens from Deepseek 4.1 Flash costs less than $15.
If you compare the cost to the price of dinner or whatever else you spend disposable income on, it can seem high but if you compare the cost to employing an engineer (don’t forget costs for payroll taxes, office space and equipment, etc) and consider the fact that the models often seem to be much faster than even expert humans, the costs don’t seem so terrible.
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