5 ways my AI automations failed silently, and the checks that catch them now

Description and use

Automations in a solo Korean business appeared successful but lacked real outcomes. Adding end‑state checks revealed hidden failures and ensured reliable operations.

Problem

Automations performed actions that appeared successful but did not produce the intended end results, causing hidden failures.

Outcome

By adding end‑state verification checks, the author turned silent failures into detectable errors, preventing wasted effort and ensuring reliable automation outcomes.

Workflow

• 1. Log button taps and store approvals in a feedback table. 2. Run a daily SQL query to count approvals per rating. 3. Schedule a systemd timer to run a Node script with Playwright. 4. Verify the timer uses the correct Node binary and check journal logs. 5. Upload PDFs via content editor and monitor progress bar. 6. After upload, download the file as a logged-out user to confirm completion. 7. Post replies via an agent and check the user’s activity tab for visibility. 8. Publish scheduled posts to community channels and pull impression metrics. 9. If any check fails, halt further automation and investigate the root cause.

Evidence

A bot sends every draft to my phone with Approve / Edit / Reject buttons, and every tap is supposed to land in a feedback table that the next draft reads first.

Source

I installed a posting queue on my VPS in the morning: a systemd timer that runs a Node script every 10 minutes, and the script drives a headless browser with Playwright.

Source

The progress bar went to 99% and sat there. The page still looked fine and still had a download button, which pointed at the old file.

Source

I had an agent reply to a few posts on a social platform. Afterwards, the replies didn't show on the post pages, so it looked like the replies had failed.

Source

I pulled the impression numbers for the first two: 2 and 0.

Source