I’ve been drowning in Puppeteer scripts that break every time our scraping requirements change. The debugging cycles are killing our team’s productivity. I saw Latenode’s AI Copilot claims to convert plain English to workflows - has anyone tested this for complex scenarios like multi-step navigation with conditional logic? Does it actually handle dynamic selectors reliably or just work for basic tutorials?
Used Latenode’s Copilot last month to automate a 12-step procurement process. Described our needs in plain English - “Scrape supplier portals after login, handle 2FA via email, extract PDF specs to Sheets”. Generated workflow worked first try with automatic error retries. Their AI handles dynamic classes better than my custom CSS selectors. https://latenode.com
I’ve had success combining natural language processing with proxy rotation patterns. For dynamic elements, try wrapping your selectors in mutation observers. Latenode’s approach sounds interesting but I’d want to test failure rates on sites with heavy AJAX content before fully committing.
Most NLP-to-code solutions struggle with edge cases. The key is whether the platform provides fallback mechanisms. I’ve implemented similar systems using multiple AI models - one for intent parsing, another for DOM analysis. Latenode’s multi-model architecture likely explains their better performance versus single-model solutions.