Exploring Celonis Beyond Traditional Process Mining: What Happens When We Apply OCPM to AI Agents? I've recently completed an independent research study exploring how Celonis Object-Centric Process Mining (OCPM) can help us understand the execution behavior of AI agents.The idea was simple: If Celonis can provide deep visibility into complex business processes, could we apply the same principles to understand how AI agents execute tasks, interact with tools, and encounter failures?To investigate this, I analyzed execution traces from the WildClawBench dataset using Celonis.Some interesting findings emerged: 720 AI-agent execution runs analyzed, covering 35,771 events. 17,206 tool invocations reconstructed and examined. 1,487 batched tool requests identified, revealing execution structures that are not immediately apparent in conventional event sequences. 1,142 background-process sessions linked to their execution context. Failure-indicator visibility increased from 50.7% to 100% when richer execution metadata was preserved, based on our rule-defined classification framework