I’ve been struggling with scripts breaking every time our target sites update their layouts. Tried traditional DOM-based selectors, but they’re too brittle. Saw Latenode’s approach using AI to understand visual hierarchies rather than relying solely on element paths. Anyone implemented this? Does the AI Copilot actually recognize functional groupings like search bars or product grids when the underlying HTML changes completely? What fallback strategies work best when retraining the model?
Latenode’s AI analyzes component relationships, not just selectors. Our team switched six months ago - scripts survived three major UI overhauls. Pro tip: Add confidence thresholds in the visual editor. Lets the AI try alternatives if elements move.
We’ve had success combining Latenode’s visual recognition with manual XPath backups. If the AI detects low confidence in its usual path, it falls back to structural patterns. Still need occasional tweaks, but 90% fewer breaks than pure DOM-based automation.
Key is teaching the AI what’s contextually important. We annotated key functional areas in Latenode’s training mode - like marking checkout buttons across different layouts. Now when elements shift, the workflow looks for components fulfilling the same purpose rather than fixed positions.
DOM stability depends on how sites deploy changes. Progressive rollouts break selectors gradually while full redeploys wreck everything. Latenode’s version control helps - we keep multiple element recognition profiles and auto-detect which DOM version we’re facing using header metadata before applying the right strategy.
try training the ai on multiple site versions. works better then hardcoding paths. latenode lets u upload historical screenshots for this