Build feedback loops into agent systems through regular
Build feedback loops into agent systems through regular review of whether agents fired, whether they produced intended outcomes, and whether conditions have changed that invalidate their design.
Why This Is a Principle
Grounds to prediction error learning (Brain as Hierarchical Prediction Machine), double-loop learning (Double-loop learning requires questioning the framework), and reflection requirement (Raw experience, without reflection, does not produce). The principle prescribes maintenance: agent systems need monitoring and review cycles. It's actionable (tells you WHAT to monitor), general (applies to all agent systems), and is the cybernetic principle applied to personal cognition.
Source Lessons
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.
Define success metrics for each agent
Every agent needs a clear definition of what success looks like in measurable terms. Without operational metrics, monitoring produces noise instead of signal.
Feedback loop hygiene
Regularly check that your feedback loops are still connected to meaningful outcomes.
Agent reliability metrics
Track how often each agent fires when it should and does not fire when it should not.