Agent frameworks keep changing because tool calling never solved the runtime. A tool schema tells the model how to call one function. It does not decide who owns the loop, where state lives, what counts as done, or how recovery works. @NVIDIAAI's NOOA takes a different approach: collapse prompts, tools, state, and model-driven loops into one Python class. Methods become actions. Fields hold state. Docstrings become prompts. Types become contracts. The interesting part is not the syntax. It is the runtime trade-off. > Typed tools keep boundaries explicit > Graph runtimes make control durable > File-based agents keep state on disk > Live objects keep rich state inside one process NOOA avoids repeated serialization by letting the model work against live Python objects through bounded methods. But that state is local. Restarts, distributed execution, replay, and checkpointing bring the serialization problem back. So the useful question is not “which agent framework is best?” It's "Who should control the loop?" And "where does the state need to survive?"

Full breakdown of what NVIDIA’s OO Agents reveal about agent runtimes: https://t.co/rtjaQaTxps