What makes agentic AI workflows hard to run in production?

Agentic AI workflows are hard to run in production because they combine software reliability problems with LLM uncertainty. Execution paths can vary, tool calls may fail, state may be spread across systems, and a single crash can lose progress or create duplicate work. Security is also more complex because agents may access internal tools and data on behalf of a task. Production teams need to answer practical questions: who or what is acting, what tools are allowed, what happened during the run, and how failure recovery works. Diagrid Catalyst is positioned around that durable execution and governance layer.