Automation · Reliability
Make it reliable¶
Reliability isn't a technology — it's a short list of "what if" answers. Here's the list, in plain words.
The checklist¶
- What if the input is garbage? Check inputs before the AI step. Wrong format or empty file → stop and flag, don't process.
- What if the AI output is wrong-shaped? Say exactly what shape you expect (sections, fields, length). If the output doesn't match, retry once, then flag.
- What if a service is down? Wait and retry once or twice, then stop and tell you. Never loop forever.
- What if it runs twice? Make re-runs harmless: check "was this already processed?" before acting. (This is the failure that sends the same email twice.)
- What if it half-finishes? Prefer all-or-nothing: build the whole result as a draft, deliver it in one final step.
- How will you know it broke? Every failure sends you a message that says what broke and which item. Silent failure is the only unacceptable failure.
Logs, minus the jargon¶
A log is just a diary the automation keeps: "3:01 processed file A. 3:02 file B skipped — empty." When something's weird three weeks from now, the diary is how you find out what happened. Ask whatever tool you use to keep one.
The maturity rule¶
New automations run with you approving every output. Only after weeks of clean runs do you let low-stakes steps through automatically — and the irreversible steps (sending, deleting, paying) keep approval forever.
If this helped
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