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  "text": "New research on Self-Evolving AI Agents.\n\nReally interesting benchmark for evaluating a critical but overlooked capability: can LLMs create reusable tools from scratch, not just use existing ones?\n\nTool-Genesis tests whether models can infer interfaces, generate schemas, and implement working code from natural language descriptions alone.\n\nWhy does it matter?\n\nSelf-evolving agents need to build their own tools, not just pick from a menu.\n\nCurrent models produce plausible-looking interfaces that quietly break downstream, revealing a key bottleneck for autonomous tool creation.\n\nThe most promising finding: closed-loop repair, letting models debug via execution feedback, dramatically improves results. But the gains are scale-dependent; smaller models can't exploit that feedback as well.\n\nPaper: https://t.co/ez1Sg1Igqn\n\nLearn to build effective AI agents in our academy: https://t.co/LRnpZN7L4c",
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