The paper proposes Agentic Data Environments that amplify agent capabilities (via information management, retrieval, and elicitation) while bounding failure consequences (via branching and data flow control).
Please don’t kill my vibe: Empowering agents with data flow control,
4 Pith papers cite this work. Polarity classification is still indexing.
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PrismaDV generates task-aware data unit tests by jointly analyzing downstream code and dataset profiles, outperforming task-agnostic baselines on new benchmarks spanning 60 tasks, with SIFTA enabling automatic prompt optimization that beats hand-written prompts.
The Redpanda Agentic Data Plane uses out-of-band metadata channels to enforce data scoping, action constraints, and tamper-proof auditing on autonomous AI agents.
citing papers explorer
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Agentic Data Environments
The paper proposes Agentic Data Environments that amplify agent capabilities (via information management, retrieval, and elicitation) while bounding failure consequences (via branching and data flow control).
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PrismaDV: Automated Task-Aware Data Unit Test Generation
PrismaDV generates task-aware data unit tests by jointly analyzing downstream code and dataset profiles, outperforming task-agnostic baselines on new benchmarks spanning 60 tasks, with SIFTA enabling automatic prompt optimization that beats hand-written prompts.
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The Importance of Out-of-Band Metadata for Safe Autonomous Agents: The Redpanda Agentic Data Plane
The Redpanda Agentic Data Plane uses out-of-band metadata channels to enforce data scoping, action constraints, and tamper-proof auditing on autonomous AI agents.
- Designing for Doubt: The Case for Informed Abstention in Autonomous Agents