Fun read, I like how overkill it is. When I was still employed, I was building our django/postgres thing locally in Docker, with 32gb of ram, and it was a wild improvement in terms of feedback loop latency over my shitty 13" intel mbp, and I think it's seriously underappreciated how important it is to keep that pretty low, or as low as is cost effective. Now that I'm not employed and don't hope to be for a while, I do think the greatest bottleneck in my overall productivity is my own discipline since I'm not compiling anything huge or using Docker. The few times I do really notice how slow it is, it's in big I/O or ram operations like indexing, or maybe the occasional xcode build, but it's still low in absolute terms and the lack of some stressful deadline doesn't have me worrying so much about it. That makes me happy in some ways, because I used to feel like I could just throw new hardware at my overall productivity and solve any issues, but I think that's true only for things that are extremely computationally expensive. Normally, I'd just spend the cash, even as a contractor, because it's investment in my tools and that's good, but the up-charge for ram and ssd is so ludicrously high that I have no idea when that upgrade will come, and the refurb older models of M1 and M2 just aren't that much lower. My battery life also sucks, but it's not $5k sucky yet. Also worth joting I'm just a measly frontend developer, but there have been scenarios in which I've been doing frontend inside either a big Docker container or a massive Tomcat java app, and for those I'd probably just go for it.