Yeah this latest generation of models (Opus 4.5 GPT 5.1 and Gemini Pro 3) are the biggest breakthrough since gpt-4o in my mind.

Before it felt like they were good for very specific usecases and common frameworks (Python and nextjs) but still made tons of mistakes constantly.

Now they work with novel frameworks and are very good at correcting themselves using linting errors, debugging themselves by reading files and querying databases and these models are affordable enough for many different usecases.

Is it the models tho? With every release (mutlimodal etc) its just a well crafted layer of business logic between the user and the LLM. Sometimes I feel like we lose track of what the LLM does, and what the API before it does.