This is a wild take. Good frameworks come with clever, well-thought-out abstractions and defensive patterns for dealing with common problems experienced when working in the space the framework covers. frameworks are also often well-documented and well-supported by the community, creating common ways of doing things with well understood strengths and weaknesses.
In some cases, it's going to make sense to drop your dependency and have AI write that functionality inline, but the idea that the AI coding best practice is to drop all frameworks and build your own vibe-coded supplychain de novo for every product is ludicrous. At that point, we should just take out the middle man and just have the LLMs write machine code to fulfill our natural language product specs.
The other thing that's dumb about this is frameworks are usually consolidating repetitive boilerplate so it's going to cost a lot more tokens for an AI to inline everything a framework does.
Yeah, definitely a stupid take from OP. LLMs are very strong at using the frameworks, it makes it easier to hire people to work on your codebase, it makes it easier for future uses of LLMs since they'll have a lot of framework details in their training data, etc.