Domain-Driven Agents

I've also been a little-d DDD fan, and we've had luck with per-entity `md` files to language-independent document domain behavior/quirks/usages.

I.e. an `Author.ts` has an `Author.md`, `Book.ts` has an `Book.md`.

For agents, we've given them a skill to read & write the `md` files:

https://github.com/joist-orm/joist-orm/blob/main/packages/co...

And so agent-written `md` updates are showing up in PRs. So far it seems useful (our main repo is a 350k LOC TypeScript monolith).

Admittedly, this is way less sophisticated (& less complicated) than the "graph of edges in/out of every bounded context" in the OP, but that is probably again my "little-d" DDD perference, where I find some of "DDD at scale" patterns lead to, imo, over-engineering.

Something i read in the earlier paragraphs about llms being easier to work with in greenfield projects…

My experience has been the opposite. They work well on existing projects but are not so great at new ones (unless you are just vibe coding something simple).

I think it has something to do with it being able to rely on years of established structure/conventions on existing projects that makes them better IME

When asked about DDD at a job interview I joked it was Debug Driven Development, when you start with empty directory and file the first bug "The app doesn't do anything. It should ..."

Non-ironically that's pretty much the way I work with AI agents now.