Or you point your Claude code at a different LLM provider. It's not complicated and there are lots of vendors (and in the open-weights space multiple vendors serving the same models competing on price). Sure DeepSeek 4 isn't quite Opus at the moment. But it's plenty good to do the work. We've got different competing front-end tools and different competing back-end providers. No one 'owns' your company. Maybe that will change as the market evolves and one of the frontier tools become so much better than one vendor will own the market. But that's not where we are now.

What happens when your engineer realizes they can make 10x more at another company? They leave and work stops. You then hire someone else or raise your pay to get better, more reliable engineers. The analogies keep going because AI is a tool, not a replacement. If it's a tool used by a non-technical person, so be it, but it's still just a tool.

In such a scenario, are you assuming Anthropic has a monopoly? Or are all LLM providers callusing on prices?

For substandard developers, yes, work stops.

I have seen many many times in microcontroller forums posts from first timers in the liking of "hello sirs i have problem please show how to do this", followed by their own reply a few hours later asking again because they were holding up, where "this" was usually something really trivial, you just needed to read the docs and the rightful answer was "did you really not try anything in 6 hours?"

Or simple economics kicks in, price/demand all that.

If hand coding pays better there will be plenty who can still do that.

The OP was asking what happens to productivity when your LLM is offline, I'd assume it isn't available yo onboard anyone at that time either.

More importantly I think, if devs become dependent enough on LLMs that they just put it aside when the model isn't available, they wouldn't be able to onboard quickly or at all.

It takes experience and a pretty deep understanding of programming in your language of choice to pick up a new code base and quickly understand how it works, the architecture(s) and pattern(s) being used, etc. Those skills would likely have been lost long before a dev simply can't work without the LLM.