That said, it's probably more dependent on what a 'full' rewrite actually is - I would be much more reluctant for a full-stack rewrite, particularly of a mature codebase with a lot of accumulated business logic. At least on the front end you can always push to move business logic upstream where it belongs.

If it helps, you can get AI to do the admin task of time tracking automatically, at least for anything that it is involved with.

Programmers are not expected to add an addendum to every file listing all the books, articles, and conversations they've had that have influenced the particular code solution. LLMs are trained on far more sources that influence their code suggestions, but it seems like we actually want a higher standard of attribution because they (arguably) are incapable of original thought.

Can mods change the linked article away from the thin blog post?

From experience, borders/cards help communicate conceptual boundaries, while whitespace helps communicate information hierarchy - Gestalt principles don't really address that distinction. For product or data-driven UI where a lot of loosely-related information/topics are shown in discrete parts of the page, cards are effective at high-level grouping. For content-driven UI, whitespace can be sufficient, and I think the article makes this clear.

Other than 'The Ultimate Developer Toolkit' (where type size is more of an issue than the card layout), I actually think the card-based version of each example layout is more compelling - easier to scan, and easier to 'chunk' - despite wanting the typography-and-whitespace alternative to be sufficient.

But there are other things, including awesome-and-dangerous nuclear waste sites, with warning messages/symbols designed to last beyond the collapse of modern civilization https://en.wikipedia.org/wiki/Long-term_nuclear_waste_warnin...

Think about how differently a current agent behaves when you say "here is the spec, implement a solution" vs "here is the spec, here is my solution, make refinements" - you get very different output, and I would argue that the 'check my work' approach tends to have better results.

From my experience with AI agents, this feels intuitively possible - current agents seem to be ok (thought not yet 'great') at critiquing solutions, and such supervisor agents could help keep the broader system in alignment.