What If an AI Agent Was Just a Python Class?
Last Updated on August 19, 2026 by Editorial Team
Author(s): Rizwanhoda
Originally published on Towards AI.
NVIDIA’s new NOOA framework collapses prompts, tools, and state into a single class and it might make you rethink your entire agent stack
AI agents have gotten weirdly complicated.
After introducing why “simple” agents quickly turn into scattered prompt/tool/state/orchestration systems, the article explains NVIDIA’s NOOA idea: represent an agent as a single Python class where state is modeled via typed fields, prompts live in docstrings, and model-controlled behavior is encoded in specific methods—so capabilities, permissions, and deterministic logic are co-located. It argues this makes state clearer, testing and debugging more natural (especially for deterministic parts), and capability boundaries easier to maintain, while also cautioning that this doesn’t automatically replace graph-based frameworks for complex orchestration needs. It reviews reported benchmark results with caveats, outlines when OO agents are a good fit versus when explicit workflow graphs still win, and closes by reframing the “real question” as how much framework a given agent truly requires—suggesting that many agents might just need an object with an LLM-wired method, not an entire new abstraction layer.
Read the full blog for free on Medium.
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