I just looked up "may you live in interesting times" and learned that it is not, in fact, originally Chinese. Per wikipedia:

> The nearest related Chinese expression translates as "Better to be a dog in times of tranquility than a human in times of chaos."

https://en.wikipedia.org/wiki/May_you_live_in_interesting_ti...

> You're assuming all women in your cohort start not pregnant. However, given a random sampling of women across the entire human race, if you have approximately 14,000 women, statistics says you'll have a baby in a month. That is to say, the chances of one of those woman being 8 months pregnant reaches close enough to 1, given about 14,000 randomly selected women.

There's a good point in here along the lines of "if you need X in a month, and someone else has something that's 90% of what you want X to be, can you buy it from them before starting any crazy internal death marches instead?"

> The real question is, how do LLMs turn the mythical man month on its head. If we accept AI generated code, can an agentic AI swarm make software faster simply by parallelizing in a way that 9 women can't make a baby in 1 month because they're am AI, not human, and communicate in a different way.

This is quite possibly only a one-time switch from a changed baseline, though. Give it a few years and "the fastest way an LLM tool can do it" will be what gets tossed out a an estimate, and stakeholders will still want you to do it in a tenth the time...

that's still one woman per pregnancy, it's not 14k women collaborating on a single pregnancy.

> You're assuming all women in your cohort start not pregnant

As far as I know, all women everywhere start not pregnant