Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures
Source
Harsh Raj, David Lee, Anas Mahmoud, Renxiong Wang, Razvan-Gabriel Dumitru, Chenguang Wang, Tong Zhao, Yunzhong He, Darvin Yi, Vipul Gupta
Author
Harsh Raj, David Lee, Anas Mahmoud, Renxiong Wang, Razvan-Gabriel Dumitru, Chenguang Wang, Tong Zhao, Yunzhong He, Darvin Yi, Vipul Gupta
Date
Terms in this piece · Glossary
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
LLM — A large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.
Why it matters
Long-horizon AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → debugging today relies on one-shot LLMA large language model — the neural network behind tools like Claude and ChatGPT, trained on huge amounts of text to predict what comes next.Full definition → judges that settle on a plausible but wrong diagnosis too early; this proposes treating root-cause attribution as a continual search problem instead, useful for anyone building agent observability tooling.
articleKRCA: An Efficient Root Cause Analysis System in Hyper-Scale Microservice Systems via Agentic AIJiamin Jiang, Jingfei Feng, Yu Luo, Qingliang Zhang, Yongqian Su, Wenwei Gu, Shenglin Zhang, Tianyu Cui, Yao Wu, Jielong Huang, Nan Qi, Dan Pei
articleSearchAuditor: Auditing and Attributing Failures in Long-Horizon Search AgentsZhixiang Liang, Yifei Liu, Yidan Huang, Haozhe Zhao, Beichen Huang, Jiaqi Wang, Nan Duan, Qiong Cao
articleEvaluating Enterprise Analytics Agents: An End-to-End, Trace-Backed MethodologyTeja Venkat Kolli, Sang Su Lee, Xueying Yan, Jessie Chen, Chi Cheng, Kartik Ravisankar, Shishir Dash, Vijay Anand Raghavan