Why do I still have to check the UI after using AI?
AI tools and automated scripts frequently make mistakes, forcing people to manually inspect the main application interface to verify that tasks actually executed correctly. This defeats the time-saving purpose of automation by requiring constant babysitting and error correction.
What people tried
Every workaround mentioned in the threads below. We haven’t tested any of them — and nobody here is claiming they worked.
Found another way around this?
Share your steps and trade-offs so fellow engineers don't have to reinvent the wheel. No account required.
- 1Switching back and forth between the interface and automation tools to manually inspect data records, formatting, and deletions.Did this help you?
- 2Manually checking and reviewing every record after it is createdDid this help you?
- 3Building custom AI agents that flag and check for data cleanliness and accuracyDid this help you?
- 4Using a middle-ground workflow where the system saves immediately but shows a summary or allows quick undosDid this help you?
In their words
Unedited, grouped by where they were said, most upvoted first within each place, each linked to the thread it came from.
“I also spend more time checking to make sure the info that AI adds in is correct. Still faster because it’s less clicks than if I were to add it manually.”source ↗
“When I skip checking for a day, I’m risking my weekend where I need to go back in and clean it up. (Been there, done that)”source ↗
Where this came up
People with this problem also raised
- 3How to know if an AI agent did the right thing
- 3How do you test if AI-generated code actually works for your business?
- 5How to track down undocumented scripts across inherited systems
- 8How to audit employee AI tools and browser extensions
- 4Why does software become just a system of record?
- 2Why does server compliance show non-compliant after updates?