An automation can work perfectly on a happy path and still fail when a field is missing, an external service is down or a person submits duplicate information. Reliability comes from designing for those moments before launch.
Start with data boundaries
Define required fields, accepted formats, maximum sizes and what should happen when input is incomplete. Validate near the entry point and again before high-impact actions.
Make retries deliberate
Retry only errors likely to be temporary. Use idempotency or duplicate checks when a repeated action could create two invoices, messages or records.
Keep a useful record
Capture enough status and diagnostic detail to investigate a failure without unnecessarily storing personal or sensitive data.
Provide a human route
High-impact decisions should have a review path or a clear fallback. Automation should communicate when it cannot safely complete a task.
Test the uncomfortable cases
Test bad input, duplicates, timeouts, permission errors and partial completion. Document who owns alerts and how the workflow can be paused.