In agentic systems, what counts as a “decision”?
That can be a hard question to answer in regards to humans, let alone agents. By some estimates, adult humans make around 35,000 decisions a day. Other estimates put our food-related decisions alone at over two-hundred per day.
https://share.upmc.com/2015/07/how-your-brain-makes-food-decisions/
It comes down to what kind of cognition you’re modeling. Are we talking about conscious deliberation? Or the automatic, procedural choices we make to keep moving through the world?
This kind of question is foundational when designing agentic systems. We don’t try to model every micro-fluctuation in user behavior as a “decision.” Instead, we draw a boundary around actionable choices — moments where our agents must commit to one option over another, and where outcomes are observable.
For every interaction each dedicated agent has with its assigned user, the agent makes five distinct classes of decisions:
Go/No-Go
Should we send something now? Agents evaluate timing: time of day, day of week, recency of prior messages, etc.
Context
What is the user doing? First app open, abandoned cart, wishlist edit — context filters the set of eligible content.
Creative Policy
Agents form a ranked policy across creative dimensions: category, value prop, incentive, CTA, tone, visuals. These aren't “templates” — they’re compositional decisions from primitives.
Item Recommendation
When catalogs are large, agents call a recommender — but only after creative policy is set, so the recommendation aligns with the core message (not the other way around).
Freshness
Even within a valid set, agents prioritize content the user hasn’t seen before, to avoid repetition and keep interactions from feeling stale.
Each of these is a point of real choice — measurable, consequential, and improvable. That’s where agentic systems need to focus: not on simulating every twitch of user behavior, but on choosing well when choice matters.
