I use LLMs every day, so I get my news from myself (I couldn't even name a Brooklyn journalist?). My experience so far is they are good for greenfield development (i.e. getting a project started), and operating within a well defined scope (e.g. please define this function in this specific place with these constraints).
What I haven't seen is any LLM model consistently being able to fully implement new features or make refactors in a large existing code base (100k+ LOC, which are the code bases that most businesses have). These code bases typically require making changes across multiple layers (front end, API, service/business logic layer, data access layer, and the associated tests, even infrastructure changes). LLMs seem to ignore the conventions of the existing code and try to do their own thing, resulting in a mess.
Def a pain point. Anecdotally Claude code and aider both can be of some help. My go to method is: dump everything in the code base into Gemini and ask for an architecture spec, then ask for implementation from aider or Claude code. This 90% works 80% of the time. Well maybe 90% of the time. Notably it can deal with cross codebase interfaces and data structures, in general, with good prompting.
Dumping it at Claude 3.7 with no instructions will 100% get random rewriting - very annoying.
What I haven't seen is any LLM model consistently being able to fully implement new features or make refactors in a large existing code base (100k+ LOC, which are the code bases that most businesses have). These code bases typically require making changes across multiple layers (front end, API, service/business logic layer, data access layer, and the associated tests, even infrastructure changes). LLMs seem to ignore the conventions of the existing code and try to do their own thing, resulting in a mess.