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[return to "Watching AI drive Microsoft employees insane"]
1. margor+72[view] [source] 2025-05-21 11:23:29
>>laiysb+(OP)
With how stochastic the process is it makes it basically unusable for any large scale task. What's the plan? To roll the dice until the answer pops up? That would be maybe viable if there was a way to automatically evaluate it 100% but with a human in the loop required it becomes untenable.
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2. diggan+f2[view] [source] 2025-05-21 11:26:06
>>margor+72
> What's the plan?

Call me old school, but I find the workflow of "divide and conquer" to be as helpful when working with LLMs, as without them. Although what is needed to be considered a "large scale task" varies by LLMs and implementation. Some models/implementations (seemingly Copilot) struggles with even the smallest change, while others breeze through them. Lots of trial and error is needed to find that line for each model/implementation :/

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3. safety+fc[view] [source] 2025-05-21 12:47:47
>>diggan+f2
I mean I guess this isn't very ambitious, but it's a meaningful time saver if I basically just write code in natural language, and then Copilot generates the real code based on that. I don't have to look up syntax details, or what some function somewhere was named, etc. It will perform very accurately this way. It probably makes me 20% more efficient. It doubles my efficiency in a language I'm unfamiliar with.

I can't fire half my dev org tomorrow with that approach, I can't really fire anyone, so I guess it would be a big letdown for a lot of execs. Meanwhile though we just keep incrementally shipping more stuff faster at higher quality so I'm happy...

This works because it treats the LLM like what it actually is: an exceptionally good if slightly random text transformer.

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