It doesn't seem like there's been a precipitous drop in resources compared to the decades of requests and warnings that have led up to this point. So what's different now, if not resourcing?
"In my experience, AI still drifts from what I meant it to do on anything bigger than building a widget."
I've had code bases with tens of thousands of lines of code built from scratch that I hand-reviewed every line of and worked with the AI to improve, and haven't had this issue. I feel like a significant part of this is due to an involved /plan stage -- going back and forth on building out a plan for what you want the AI to do involves surfacing the assumptions that you would have called drift if you asked them to implement it directly from your prompt.
Once the plan has been refined and is what I want it to be, getting it to implement everything in TDD style has for the most part given me 100% working code, as I wanted it to be, without issues. It definitely helps that I'm a principal-level engineer with extensive architectural experience -- but if you're able to tell the AI in detail what you want, have it ask questions for clarifications, and read through a plan before getting it implemented, and have a solid testing plus manual qa process (automated by chrome devtools mcp) in place, I've find that you can one-shot complex features, rewrites, and even not-insignificant applications that would have taken days to write by hand in a few hours.
I love this response. On a slightly smaller scale, there are also ideas of protein interaction-network computational 'circuitry' -- I think that showing that folding can also compute is a nice addendum to this.