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A study from researchers at Princeton University and UC San Diego finds that so-called skills make AI agents better mainly through structured workflows, not through added knowledge. But as the skill library grows, agents have a harder and harder time finding the right set of instructions.
The article Study explains why AI agents benefit from "skills" and when they fail appeared first on The Decoder.
<p>Picture this scenario: An Anthropic Skill scanner runs a full analysis of a Skill pulled from ClawHub or skills.sh. Its markdown instructions are clean, and no prompt injection is detected. N [...]
<p>One major challenge in deploying autonomous agents is building systems that can adapt to changes in their environments without the need to retrain the underlying large language models (LLMs). [...]
<p>Across 116 enterprises, agents are in production and so are the incidents: A majority have already had a confirmed agent security event or a near-miss. Two-thirds of enterprises enforce scope [...]