I’ve been looking at different ways to handle repetitive form filling across multiple sites, and the whole idea of describing what you need in plain English and getting a working automation back sounds almost too good to be true. Has anyone actually used AI copilot workflow generation for something like this?
My concern is whether it actually understands the nuance of what I’m trying to do. Like, I need to fill out forms with conditional logic—if field X contains Y, then skip field Z. Does the copilot handle that, or does it just generate something basic that needs tons of manual tweaking?
I’m also wondering about data scraping combined with form filling. The workflow would need to pull data from one site, transform it somehow, then use it to fill forms on another site. That’s not trivial. How many iterations does it usually take before you get something that actually works?
I’ve used the copilot for exactly this kind of thing. The key is being specific about what you describe. Don’t just say “fill form with data”. Say something like “pull product names from the CSV, check if price is above $100, and only fill the form if it is.”
The copilot generates a solid starting point. It’s not perfect right out of the box, but it handles conditional logic better than you’d expect. I’ve gone from description to working automation in a single iteration maybe 60% of the time.
For data transformation between sites, I usually add a step to clean the data before form submission. The copilot can handle this if you describe it clearly.
Latenode does this really well because the visual builder lets you tweak the generated workflow without starting from scratch. You can see what the copilot created, then adjust specific steps.
I’ve had mixed results with plain English descriptions. The issue I ran into was that my description made sense to me, but the copilot interpreted one part differently than I expected. It generated a workflow that filled the form, but in the wrong order.
What helped was breaking down my request step by step. Instead of one long description, I described the form filling in stages. First, handle the basic fields. Then, second, handle conditional logic. That gave the copilot clearer instructions.
For data pulling and transformation, I found it relies a lot on how well the target site’s HTML is structured. If the site uses standard form elements, it works great. If there’s a ton of JavaScript rendering, you might need to help it along.
I’ve tested this with customer intake forms and competitor price tracking. The reliability depends heavily on how consistent your source data is. When the data structure is predictable, the copilot-generated workflows run without issues. But when you’re dealing with dynamic content or inconsistent formatting, you do end up tweaking things manually.
The conditional logic works, but you need to be explicit about edge cases. The copilot won’t anticipate problems you don’t mention. That said, once you have a working workflow, using the visual builder to adjust it beats writing code from scratch. The learning curve for understanding what the copilot generated is actually shorter than I expected.
The accuracy rate improves significantly if your description includes examples. Instead of saying “validate email addresses”, say “validate email addresses like [email protected]”. The copilot uses these examples to infer intent more accurately.
One thing to watch: the copilot generates workflows optimized for the visual builder, not for raw performance. That’s actually a strength because subsequent edits are easier. But if you need heavy customization, you’ll eventually write some JavaScript to handle edge cases.
used it for form fills. works best w/ specific descriptions. expect 1-2 tweaks before production. conditional logic is solid if you explain clearly. data transform between sites needs manual setup sometimes.