problem_kicker
Traditional application logs are often insufficient for agentic systems because one user request can trigger planning, policy decisions, multiple tool calls and asynchronous state changes.
DEMAND LANGUAGE / REAL-WORLD PROBLEM
“It works in the demo — but will it work in daily operations?”
“How do we measure whether the problem is actually solved?”
WHAT CAUSES THIS?
Logs capture text but not machine identity and capability.
architecture_for AI AGENT AUDIT TRAILS
We define a minimal evidence schema that connects actor, owner, version, policy, capability, resource, execution, result and verified state while minimizing unnecessary sensitive payload retention.
Audit storage requires access control, integrity protection, retention policy and redaction. Evidence should be sufficient for reconstruction without becoming a new uncontrolled copy of sensitive data.
Use structured events and asynchronous durable pipelines so evidence capture does not dominate action latency. Monitor dropped-event and lag metrics explicitly.
AI agents · audit trail · observability · policy · provenance
failure_kicker
measure_kicker
verify_intro
CTO / CIO FAQ
No. Operational auditability can be built from inputs, policy decisions, capabilities, tool calls, outputs, versions and verified state without storing private reasoning traces.
Append-only controls, integrity hashes/signatures, restricted write paths and independent retention can make unauthorized alteration detectable.
That depends on business, contractual and regulatory requirements; the architecture should make retention policy explicit rather than accidental.
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