I’ll add to this, many places in America and I’m assuming other places in the world, society might not be serving you. Where I grew up I knew multiple people living off well water because there was no water main anywhere near them and the closest city/utility said they would be happy to install a pipe in their direction but at cost to them.

I would also argue living off grid isn’t abandoning society if you’re still paying taxes.

Sort of. Government and society have significant overlap but arent necessarily the same.

I have no sources for this but just the understanding I get from talking with some folks born after 2000. Most people are online or doing more individualistic activities so meeting single people organically is difficult. Dating apps are wildly skewed based on gender and have changed peoples dating behavior. I think there are other factors too but I think the combo of those two have left a lot of people discouraged and exhausted trying to date

I don’t know, I could be wrong but I think one of the key aspects of system design which I don’t know if there is a lot of training data for us the “why” behind decisions. Separating out good design from bad isn’t always black and white and like the article mentions it’s about managing complexity and trade offs. It’s hard to capture in code/training data “we designed everything in a certain way but compromised in this one area because we were under time constraints and assumed we could fix it later”

A fun little exercise you can do is design a system and write some code and then ask LLM to explain why you wrote it that way. Results are varied and interesting but in my experience rarely capture the actual why behind decisions.

Interestingly, while it may not match the reasoning that I have, I find that it usually comes up with things that I should have thought of.

100% getting everything working for TidalCycles was rough, I remember needing to get Haskell, TidalCycles, and SuperCollider all communicating with each other and on the correct version. Once it was installed and working it was pretty solid but lots of headaches getting to that point. Maybe it’s better now though

I think the biggest issue might not be the immediate team but upper leadership. Companies which have mandated AI usage override a lot of what an individual or individual team wants. If that’s the case then it would be a lot like fighting the ocean, especially if your immediate team sees having AI write docs as an easy way to move the needle on LT’s AI monitoring dashboard.

But doesn’t China have the largest rollout of solar in the world?

I believe so, They have also increased their coal consumption.

The #1 increase in world electricity demand is people rising out of poverty. China has been producing the most solar in the world and still hasn't been able to cover their own demand increase with it. Eventually that form of growth will slow down. Sustainability should always look at the second derivative.

It’s worth pointing out that already last year while China’s coal power capacity grew their actual power production from coal fell.

Also need to reduce use of coal in steel production too, yet.

Maybe we should be looking inward as to why solar isn't more easily deployable in the US. Local zoning, permitting, and community opposition are some of the top road blocks there...

Solar has a problem so it's a vanity project, but coal has a billion problems but it doesn't matter because you can adjust the output?

Like it genuinely sounds like you're suggesting our current terrible system shouldn't even be attempted to be improved unless there's a magic perfect solution to replace it.