What guardrails do you add before an automation touches real users?

After reading the last few discussions, one thing is clear:

most failures don’t come from bad ideas—they come from unexpected inputs, edge cases, and silent failures.

Before deploying an automation that interacts with real users or clients, what guardrails do you usually put in place?

Examples I’ve seen:

Validation layers before workflows run

Human-in-the-loop approvals for edge cases

Confidence thresholds or fallbacks

Monitoring / alerts instead of “fire and forget”

Curious what’s non-negotiable in your builds 👇

4 comments

skool.com/ai-automation-society

A community built to master no-code AI automations. Join to learn, discuss, and build the systems that will shape the future of work.

Leaderboard (30-day)

🔥

+11275

🔥

+7844

+3365

🔥

+3020

+2335