Measuring Agents in Production

Melissa Z. Pan; Negar Arabzadeh; Riccardo Cogo; Yuxuan Zhu; Alexander Xiong; Lakshya A Agrawal; Huanzhi Mao; Emma Shen; Sid Pallerla; Liana Patel; Shu Liu; Tianneng Shi; Xiaoyuan Liu; Jared Quincy Davis; Emmanuele Lacavalla; Alessandro Basile; Shuyi Yang; Paul Castro; Daniel Kang; Koushik Sen; Dawn Song; Joseph E. Gonzalez; Ion Stoica; Matei Zaharia; Marquita Ellis

arXiv · 2512.04123

Measuring Agents in Production

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Abstract

LLM-based agents already operate in production across many industries, yet we lack an understanding of what technical methods make deployments successful. We present the first systematic study of Measuring Agents in Production, MAP, using first-hand data from agent developers. We conducted 20 case studies via in-depth interviews and surveyed 86 deployed systems practitioners across 26 domains. We investigate why organizations build agents, how they build them, how they evaluate them, and their top development challenges. Our study finds that production agents are built using simple, controllable approaches: 68% execute at most 10 steps before human intervention, 70% rely on prompting off-the-shelf models instead of weight tuning, and 74% depend primarily on human evaluation. Reliability (consistent correct behavior over time) remains the top development challenge, which practitioners currently address through systems-level design. MAP documents the current state of production agents, providing the research community with visibility into deployment realities and underexplored research avenues.

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Melissa Z. Pan, Negar Arabzadeh, Riccardo Cogo, Yuxuan Zhu, Alexander Xiong, Lakshya A Agrawal, Huanzhi Mao, Emma Shen, Sid Pallerla, Liana Patel, Shu Liu, Tianneng Shi, Xiaoyuan Liu, Jared Quincy Davis, Emmanuele Lacavalla, Alessandro Basile, Shuyi Yang, Paul Castro, Daniel Kang, Koushik Sen, Dawn Song, Joseph E. Gonzalez, Ion Stoica, Matei Zaharia, Marquita Ellis. 2025-12-02. Measuring Agents in Production. https://arxiv.org/abs/2512.04123

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