[throwaway173738]

The concept of a small module is an architecture invariant. You’re making that decision, not the LLM. And you’ve made that decision because the machine is not good at certain things. You’re doing that because you can’t trust the LLM to make that decision on its own.

[ChicagoDave]

I’m doing it because as a DDD adherent, I’ve been building software that way for 15 years without GenAI and now with GenAI I can do it faster.

You can’t play whack-a-mole with GenAI. You have to start from well-known principles and watch everything it produces. Every module or bounded context has to have its own invariants.

You can’t fully automate software engineering with GenAI. It seems the vast majority of GenAI users think they can and end up in the same place as the OP.

Maybe learn Domain-Driven Design, Event Sourcing, and then try again. The results will be dramatically improved.

https://devarch.ai/

[peterbell_nyc]

Love the DDD callout. I have explicit steps to review and rate delta's to the ubiquitous language and one of my architectural reviewers will often engage with me about where the bounded contexts should be and will probably the translation layers.

I find the more good practices I add to my envision/scope/spec/build/test/deploy loops the happier I am with the outcomes.

I will say that I am finding the actual code to be somewhat ephemeral for me - the more precise the specifications are and generally the tighter and more elegant the design is, the less the code matters as a long term artifact.

I'm not at the "code is assembler" point yet - but I could see that with more, richer specs I could end up there. Of course the specs are then substantial, but declarative specs can be robust and unambigous (with sufficient read teaming review) and - like domain specific languages - reduce the accidental complexity of the syntax when compared to an implementation in a given language.

There are exceptions to all of this, but it's fascinating to see how it's evolving!