I’ve been looking at ways to speed up our web automation work without having to build everything from scratch. The idea of describing what I need in plain English and getting a ready-to-run workflow sounds almost too good to be true, but I’m curious if anyone’s actually tried this.
We’ve got some repetitive tasks—logging into sites that don’t have APIs, extracting data from pages that are behind authentication, that kind of thing. Usually I’d end up writing a lot of boilerplate code or debugging brittle selectors that break as soon as a site redesigns.
I found some info about using AI to generate these workflows automatically from descriptions. The promise is that you describe what you need—like “log in to this site, navigate to the reports section, extract the table data”—and the system generates the actual browser automation code.
But here’s what I want to know: does this actually hold up when the sites start changing their layouts? And how much customization do you typically need to do after the initial generation? Is it worth the time investment compared to just writing the automation myself?
I’ve been using Latenode’s AI Copilot for exactly this kind of work, and honestly it saves me hours each week. I describe the workflow—like you said, login, navigate, extract—and it generates something that actually runs on the first try most of the time.
The key thing is that it’s not just generating random code. It understands headless browser actions and creates workflows that account for page load times, dynamic content, that kind of stuff. When sites do redesign, you can adjust the workflow without rebuilding everything.
What impressed me most was how it handles the unglamorous stuff—waiting for elements to load, retrying failed clicks, capturing screenshots for debugging. That’s the work that usually takes days.
The reliable part comes from the fact that it’s learning from the context you give it. If you say “wait for the table to load,” it doesn’t just blindly click. It understands the intent.
Worth trying if you’ve got repetitive browser tasks piling up. Check it out at https://latenode.com
I’ve worked with a few different approaches here. Plain text to automation can work, but it really depends on how specific your descriptions are. The better you describe edge cases—what happens if the button doesn’t load, what timeout values you need—the more reliable the output.
One thing I learned the hard way: these systems work best when you’re describing what the user sees, not how you think it should be coded. Instead of “click the element with id submit-btn,” say “click the submit button after the form is filled.” That context actually matters.
For authentication flows specifically, I found that being explicit about what you’re logging into and what you expect to see on the next page reduces failures. The automation engine uses that to validate it’s working correctly.
Site redesigns are always going to be a problem with any automated approach. But if your workflow is well-documented with clear success criteria at each step, it’s often just tweaking a few selectors rather than rewriting the whole thing.
I tested this approach on a project where we needed to scrape pricing data from several e-commerce sites daily. The workflow generation got us 80% of the way there in minutes instead of hours. The remaining 20% was validating that selectors matched the actual page structure and setting appropriate wait times.
What worked well was using screenshots and explicit success criteria. Telling the system “the page has loaded when you see the product list” gives it something concrete to work with. Without that, it makes assumptions that don’t always match reality.
The unreliable part was mostly around handling unexpected page states—things like popup dialogs or slow content loading. I had to add error handling and retry logic after the initial generation. That’s normal though. You’re not replacing development, you’re automating the boilerplate so you can focus on the tricky parts.
Done this. Works for basic flows but you’ll need tweaks for edge cases. Takes more time than you’d think to get the descriptions right so the system understands what your really want. Still faster than coding from scratch tho.
Works well for standard flows. Be specific about validation steps and expected outcomes.
This topic was automatically closed 24 hours after the last reply. New replies are no longer allowed.