Agentic workflow automation keeps failing at the same step and it is not the model

I think we blame the model way too much for this. A lot of enterprise deployment problems seem to happen because the agent is working from a process map that was never actually accurate in the first place. The docs say four steps. Cool. Then the real process has a manual reconciliation nobody documented, an exception path that gets used 20% of the time, and some random handoff happening over email. At that point it is hard to call this a model problem. Agentic workflow automation seems way more bottlenecked by context than capability. And that gets awkward when most organizations cannot even produce an accurate process map when asked. What is interesting is that this starts pointing toward process intelligence rather than just agent frameworks. Celonis and Skan AI seem pretty relevant here. Maybe the missing piece for enterprise deployment is not making the agent smarter. Maybe it is finally giving the agent the context of how the process actually works.