What an AI coding agent audit trail should record
By the AgentReceipt team · Updated 13 November 2026
If AI agents write part of your code, someone will eventually ask: who asked for this, what did it change, and did anyone check? An audit trail is the answer. This is what a useful one contains, and what it should leave out.
Record these things
A trail is only useful if each entry answers the questions a reviewer or an auditor will ask.
- Who started the session, and when
- The prompt that started it
- Every file that changed, with the lines added and removed
- Anything risky that was found, and why it counts as risky
- Which pull request or commit the work ended up in
Use fixed rules, not a model’s opinion, to flag risk
A flag you cannot explain is hard to trust. Fixed rules, such as “a test file was deleted” or “a secret-like value appears in the diff”, give the same answer every time and can be explained in one sentence. That matters when someone asks why a change was flagged.
Do not record secrets
Prompts and diffs sometimes contain keys and passwords. A trail that stores them becomes a new place for them to leak from. Remove secret-like values before anything is written down, and keep the trail itself short-lived.
Make entries hard to change after the fact
A record that anyone can edit proves little. Store each entry as one unit that is not edited once saved, so that what you read later is what was written at the time.
Decide how long to keep it
Keeping everything forever adds cost and risk. AgentReceipt keeps receipts for seven days in the dashboard. After that, the manager receives an emailed report with one PDF per employee, and the receipts are deleted. That keeps a copy where your company chooses to store it, and keeps the hosted copy small.