Agents for stochastic versus deterministic work

Posted some of my latest thinking on when AI agents are additive to the automation and controls workflows already provide. Feel free to drop your own comments or thoughts:

Great take! I really like the framing: deterministic rules for objectively knowable, 100% certain decisions; traditional predictive AI for proactive decisions with measurable confidence; and GenAI for subjective assessment with validation. These are all tools we can apply to any problem. The real leverage comes from knowing when—and how—to use them together. Any single approach on its own will fall short. Also , there are options to combine them to be more predictable, for example using business rules to bound or validate a GenAI assessment, ensuring LLM outputs stay within defined tolerances.

Great HTOTW, Don. Many are treating Agents as standalone brains but in an enterprise context, an agent without a workflow is just a liability. From a technical standpoint, the real magic happens when we wrap an LLM in a case lifecycle. By using the case as the source of truth for state and context, we ensure the agent operates within defined Guardrails, turning probabilistic AI outputs into deterministic business outcomes.

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