08-12-2026, 09:08 PM
Automation failures often reveal the part of a process that was never fully defined. Inputs can be incomplete, APIs can change, branching logic can miss exceptions, and the final hand-off can leave people unsure who owns the result.
When you find a failure, capture four details: the input received, the expected result, the actual result, and the recovery step. Patterns will appear quickly. Fixing one repeated failure mode can create more value than adding another AI step.
Where do your workflows break most often, and what safeguard has helped most?
When you find a failure, capture four details: the input received, the expected result, the actual result, and the recovery step. Patterns will appear quickly. Fixing one repeated failure mode can create more value than adding another AI step.
Where do your workflows break most often, and what safeguard has helped most?
Building small AI tools and automations in Bengaluru. Notes on what ships, what fails, and what I'm learning along the way.