Cognitive agent: a repeatable process you design to handle
Cognitive agent: a repeatable process you design to handle recurring decisions, consisting of a trigger (situation that activates it), a condition (what must be true for it to fire), and an action (what it does when triggered and condition is met)
Why This Is a Definition
This is a precise, self-contained definition that establishes the semantic boundary of 'cognitive agent' by naming the term, stating its genus (repeatable process), and providing its differentia (trigger-condition-action structure). It's presented as the fundamental definition in the lesson's primitive section and is consistently referenced throughout.
Source Lessons
An agent is a system that acts on your behalf
Cognitive agents are repeatable processes you design to handle recurring decisions.
Agent components: trigger, condition, and action
Every agent has a trigger that activates it, a condition that validates it, and an action it takes.
Agents reduce decision fatigue
When an agent handles a recurring decision you preserve energy for novel decisions.
Agent reliability matters more than agent sophistication
A simple agent that fires consistently beats a complex agent that fires intermittently.
Agent thinking is systems thinking applied to yourself
Designing agents for your own cognition is applying systems design to the most important system you manage.
The trigger audit
Regularly review your triggers to ensure they are still relevant and well-calibrated.
Multiple agents must coordinate to be effective
When you run several cognitive agents they need to work together not interfere with each other.
Agents have a lifecycle from creation to retirement
Every agent is created, deployed, maintained, and eventually retired.
Agent scope should be narrow
Each agent should handle one specific situation — multi-purpose agents are fragile.
Agents must be specific and testable
Vague agents do not fire reliably — specificity is required.
Designed agents replace default agents
Every deliberate agent you create replaces an unconscious default.
Decision agents
Agents for recurring decision types like buy-versus-build or accept-versus-decline.
Reliable triggers are specific and observable
A trigger must be something you can detect consistently.
Agent effectiveness metrics
Effectiveness means your agent produces the intended outcome, not just that it runs.
Time-to-fire metrics
Track how quickly each agent responds to its trigger.
Journaling as manual monitoring
Written reflection is the oldest and most versatile form of self-monitoring.
Agent maintenance schedule
Agents need regular maintenance — scheduled reviews prevent gradual degradation.
Agent retirement criteria
Define clear criteria for when an agent should be retired rather than maintained. Without explicit retirement criteria set in advance, you will hold onto agents long past the point where they serve you — because the sunk cost of building them, the identity you attached to them, and the absence of a forcing function all conspire to keep dead agents on life support.
The agent lifecycle mirrors the learning lifecycle
The way you create, maintain, and retire agents mirrors how you learn, practice, and let go of knowledge. Recognizing this parallel turns agent management into a form of self-directed development.
Integration optimization
Optimize how agents connect and hand off to each other, not just how each agent performs in isolation.