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Written by Max Zeshut
Founder at Agentmelt
A durable, tamper-evident, append-only record of every consequential decision and action an AI agent takes — the agent's answer to 'what did you do, and why?' It is not the same as application logs: ordinary logs are for debugging and get rotated away, while an audit trail is for accountability and must survive the incident, the audit, and the retention window a regulator asks about. A useful entry captures, per action: the *trigger* (what caused the run), the *context* (inputs and retrieved data the agent saw), the *reasoning* (trace of the plan and tool calls, not just the final action), the *action and its authority* (what it did, under which identity and scopes), and the *outcome*. To be trustworthy it must be tamper-evident — append-only storage, ideally hash-chained so altering history is detectable — which is where it meets Non-Repudiation. Under the EU AI Act, deployers of high-risk systems are specifically required to keep the logs their AI automatically generates.
An accountable audit-trail entry: trigger = scheduled 2am reconciliation; context = bank feed hash + 3 flagged transactions; reasoning = trace showing the agent matched 2 and escalated 1; action = wrote to staging_ledger under identity 'recon-agent' scope 'ledger:write:staging'; outcome = 1 item sent to an approval gate; signed and hash-chained to the prior entry.