Measuring Agents in Production
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 306 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 under-explored research avenues.
Keywords
Cite
@article{arxiv.2512.04123,
title = {Measuring Agents in Production},
author = {Melissa Z. Pan and Negar Arabzadeh and Riccardo Cogo and Yuxuan Zhu and Alexander Xiong and Lakshya A Agrawal and Huanzhi Mao and Emma Shen and Sid Pallerla and Liana Patel and Shu Liu and Tianneng Shi and Xiaoyuan Liu and Jared Quincy Davis and Emmanuele Lacavalla and Alessandro Basile and Shuyi Yang and Paul Castro and Daniel Kang and Joseph E. Gonzalez and Koushik Sen and Dawn Song and Ion Stoica and Matei Zaharia and Marquita Ellis},
journal= {arXiv preprint arXiv:2512.04123},
year = {2026}
}