[simonra]

As long as the odds are good enough (and/or you know the distribution), there is nothing wrong in relying on and profiting from stochastic systems despite not every outcome being positive. What matters is the sum of outcomes, not the individual ones.

It means you need to be able to handle failure, but you should always have a good grip on how to correct if you intend to set things out in the real world which messes up everything always anyways.

[kennywinker]

Sure, but that’s not how most llm coding is done, because if a human has to carefully supervise the llm then what’s the point - might as well write it yourself.

Add to that, we’re very good at anthropomorphizing, and very bad at supervising systems that are usually right. Makes for a mess.

Oh, and this all relies on the ai providers not changing things up behind the scenes and feeding you a dumber model sometimes.