Dspys advertising aside, imho it is a library only for optimizing an existing workflow/ prompt and not for the use cases described there. Similar to how I would not write "production" code with sklearn :)

They themselves are turning into wrapper code for other libraries (e.g. the LLM abstraction which litellm handles for them).

Can also add:

Option 3: Use instructor + litellm (probabyly pydantic AI, but have not tried that yet)

Edit: As others pointed out their optimizing algorithms are very good (GEPA is great and let's you easily visualize / track the changes it makes to the prompt)