What is an audit trail for AI agents?
An audit trail for an AI agent is a record of what the agent did, who asked it to, and what happened. It lets you answer “who approved this?” and “what changed?” after the fact.
What should an audit trail record?
- The agent: which one acted.
- The person who instructed it.
- The action: what it tried to do, including tool calls.
- When it happened.
- The result, and any error.
- Any approval, override or interruption.
Why does it matter?
A record lets you debug a bad change, hand work to someone new, and show how a decision was made. For some teams it is also a compliance requirement.
What makes an audit trail useful?
- It writes itself. Nobody has to remember to log.
- People can read it, not just machines.
- It lives next to the work, not in a separate tool.
- You can export it.
How does Friday record this?
Every action in a shared session traces back to the person who asked for it. The session keeps a log of who instructed what, what the agent did, what each tool returned, and when. People who join late get a short catch-up digest, and you can export the log.
History is kept for 30 days on Free, 1 year on Pro, and without limit on Max.
What does an audit trail not do?
A log shows what happened. It does not make an agent right. Review still matters, as in how to review AI-generated pull requests.
Common questions
Is a chat history an audit trail?
Not usually. A chat log records messages. An audit trail also ties each action to the person who asked for it, and to the tool calls and results.
How long is the record kept?
It follows your plan: 30 days on Free, 1 year on Pro, and unlimited on Max.
Can I export it?
Yes. You can export the session log.