AI Automation: Did Errors Stop or Did You Just Stop Finding Them?
Recent-Ball543 · reddit · 2026-07-31
A user shares thoughts on verifying AI automations. He interviewed people running AI automations and found that the line people draw isn't risky vs. safe, but verifiable vs. not. People happily automate high-stakes work when the result is checkable, and refuse low-stakes work when it isn't. Almost nobody trusts the agent's own report, and everyone had built similar workarounds: log at the tool layer, compare results against approved source data, keep read-only by default, record what was requested separately from what executed. He poses three questions: 1. If you scaled back checking, did you ever go back and verify a sample? What did you find? 2. Has an automation ever reported success while doing the wrong thing, and how long before anyone noticed? 3. What would you need to see to trust a check more than your own spot audit?
Related event: The Biggest Hidden Danger in AI Automation: Unverifiable Results(2 posts)→
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