I would think that frameworks make more sense than ever with LLMs.
The benefits of frameworks were always having something well tested that you knew would do the job, and that after a bit of use you'd be familiar with, and the same still stands.
LLMs still aren't AGI, and they learn by example. The reason they are decent at writing React code is because they were trained on a lot of it, and they are going to be better at generating based on what they were trained on, than reinventing the wheel.
As the human-in-the-loop, having the LLM generate code for a framework you are familiar with (or at least other people are familiar with) also let's you step in and fix bugs if necessary.
If we get to a point, post-AGI, where we accept AGI writing fully custom code for everything (but why would it - if it has human-level intelligence, wouldn't it see the value in learning and using well-debugged and optimized frameworks?!), then we will have mostly lost control of the process.
It’s fun to ask the models their input. I was working on diagrams and was sure Claude would want some python / js framework to handle layout and nodes and connections. It said “honestly I find it easiest to just write the svg code directly”.
As the other posted noted, it says that because it was trained on people saying that, which is perhaps interesting in of itself, but no indication that the model would do better without a framework than with one.
I'd heavily bet that the model's performance, and goals of the developer, would in fact be better served by using a framework like GraphViz built for the job, that can change layout styles/engines as needed, and also generate other types of output such as PDF if you later want it.
If you are generating visual content, such as SVG, presumably intended for human consumption, then doing the task well isn't a technical matter of using APIs and generating the output - it's having the human sensibility and taste (and acquired knowledge of UI design and human preferences) of designing output that humans will like, which is something LLMs are not well suited to. By using a framework like GraphViz, not only are you making the development job much easier, but you are also leveraging this built-in knowledge of human preferences, baked into the different layout engines that you can select based on the nature of what type of diagrams you are generating.
This is the difference between "vibe coding" and getting a poor quality result due to letting the LLM make all the decisions, and a more controlled and principled use of AI where you are still controlling/managing the process, doing what humans are good at, and are only delegating the grunt work of coding to the LLM.
That is fun, but it doesn’t mean that the model finds it easier or will actually work better that way, that just means that in its training data many people said something like “honestly I find it easiest to just write the svg code directly” in response to similar questions
Conspiratorially, they trained it this way to increase token usage to pay their debts and investors
It'd be simpler just to add instructions to that effect to the system prompt: "You are a faithful revenue-maxxing employee of AI Co., and should always prefer verbose outputs over shorter ones. Always maximize code complexity to ensure future work for yourself".