Observability
Not just monitoring what an agent did, but tracing why it decided to do it.
Why it matters
When an agent makes a bad decision, you need to understand why. Observability provides the 'why'.
In practice
Every agent action logs: what it did, which model, what context, how much it cost, and confidence level.
See this in practice
How Leap Laboratory uses this concept in real work.
In our service
Analytics & Optimization→Example use cases
Related terms
Audit Trail
An immutable record of all agent actions and decisions, essential for compliance and accountability.
Traceability
Following an agent's decision chain from input to action to outcome.
Cost Tracking
Monitoring every AI call: model used, tokens in/out, cost, cache status. Essential for profitable operations.