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Agents Are Not Enough

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arxiv 2412.16241 v1 pith:3YMX45MR submitted 2024-12-19 cs.AI cs.HCcs.MA

classification cs.AIcs.HCcs.MA
keywords agentswhatusercurrentmakealoneappealingartificial
verification ladder T0 review T1 audit T2 compute T3 formal
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In the midst of the growing integration of Artificial Intelligence (AI) into various aspects of our lives, agents are experiencing a resurgence. These autonomous programs that act on behalf of humans are neither new nor exclusive to the mainstream AI movement. By exploring past incarnations of agents, we can understand what has been done previously, what worked, and more importantly, what did not pan out and why. This understanding lets us to examine what distinguishes the current focus on agents. While generative AI is appealing, this technology alone is insufficient to make new generations of agents more successful. To make the current wave of agents effective and sustainable, we envision an ecosystem that includes not only agents but also Sims, which represent user preferences and behaviors, as well as Assistants, which directly interact with the user and coordinate the execution of user tasks with the help of the agents.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Agentic Workflows for Conversational Human-AI Interaction Design

    cs.HC 2025-01 conditional novelty 5.0 of 10

    A four-cycle design study found that agentic workflows with contextualization, goal formulation, and prompt articulation help users and designers manage ambiguity and transience in conversational AI.

  2. Language Games as the Pathway to Artificial Superhuman Intelligence

    cs.AI 2025-01 conditional novelty 4.0 of 10

    A position paper arguing that open-ended language games with fluid roles, varied rewards, and evolving rules can drive expanded data reproduction and thus a path to artificial superhuman intelligence.

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