[isodev]

This kind of complexity is unfortunately also embedded into model training data.

Left unchecked, Claude is very happy to propose "robust, scalable and production ready" solutions - you can try it for yourself. Tell it you want to handle new signups and perform some work like send an email or something (outside the lifecycle of the web request).

That is, implying you need some kind of a background workload and watch it bring in redis, workflow engines, multiple layouts for docker deployment so you can run with and without jobs, obscene amount of environment variables to configure all that, create "fallbacks" and retries and all kinds of things that you will never spend time on during an MVP and even later resist adding just because of the complexity and maintenance they require.

All that while (as in the diagram of the post), there is an Erlang/Elixir app capable of doing all that in memory :).