Nvidia released NOOA, a framework that represents AI agents as single Python classes, consolidating capabilities, state, and prompts into one unified structure to reduce fragmentation in agent development. On SWE-bench Verified, NOOA achieved 82.2% accuracy with GPT-4o using 29 LLM calls and roughly 1.1M tokens per task, compared to competitors requiring 66 calls and 2.2M tokens for 78.2% accuracy. The centralized approach makes agents easier to inspect and audit but concentrates security risks and may blur distinctions between deterministic and probabilistic code paths.
Something Big Is Happening·1 month ago·
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Matt Shumer describes a technique called a Gauntlet Loop for improving AI agent outputs by having builders and independent critics repeatedly compare work against concrete reference examples until reaching a quality bar. He generated a 55,000-line Call of Duty game using Claude Opus 5 with this method, achieving results higher quality than typical AI demonstrations. The approach applies broadly to code, design, writing, and other outputs, with key principles including separating builder and critic roles, setting ambitious goals with concrete quality standards, and allowing agents to decompose work independently rather than following prescribed steps.
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