Why Every AI Agent Team Needs a Cron Job Audit Trail

Fazm Team··3 min read
cron-jobsaudit-trailmonitoringreliabilityscheduled-tasks

Silent Failures Are the Default

You set up a cron job for your AI agent. It runs every night at 2 AM - cleaning up files, syncing data, generating reports. It works great for a week. Then it silently stops working and nobody notices for a month.

This is the default state of scheduled agent tasks. Without an audit trail, you have no way to know whether your cron jobs are running, succeeding, or quietly failing.

What Goes Wrong

Cron jobs fail in ways that are uniquely hard to detect:

  • The job runs but does nothing. The agent starts, finds no work to do (because the input source changed), and exits cleanly. Exit code 0. No error. No output. No value.
  • The job partially completes. The agent processes 8 out of 10 items, hits a rate limit on items 9 and 10, and exits. You get 80% of the expected results and never notice the missing 20%.
  • The job runs but produces wrong results. The agent's context has drifted, or a dependency changed, and the output is subtly wrong. No errors in the logs.
  • The job stops being scheduled. A system update, a reboot, a launchd config change - the cron job simply stops firing and nobody checks.

What an Audit Trail Needs

Every scheduled agent task should log:

  • Run timestamp - when the job started and finished.
  • Input summary - what data the job found to process.
  • Output summary - what the job produced or changed.
  • Comparison to previous run - is this run's output significantly different from the last one? If the job usually processes 100 items and today it processed 3, that is a signal.
  • Health check - a simple heartbeat that says "this job is still being scheduled and still running."

Five Logs Every Cron Agent Needs

  1. Execution log - did it run at all?
  2. Input log - what did it receive?
  3. Decision log - what did it choose to do with each input?
  4. Output log - what did it produce?
  5. Comparison log - how does this run compare to the baseline?

Set up alerts on the absence of logs, not just the presence of errors. The most dangerous failure is the one that produces no signal at all.

Fazm is an open source macOS AI agent. Open source on GitHub.

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