I’ve been experimenting with describing browser tasks in plain text and letting the AI generate the workflows automatically. On paper, it sounds amazing—just type what you want and get a ready-to-run automation. But I’m curious about real-world reliability.
I tried having the copilot generate a workflow to log into a site, navigate through a few pages, and extract some data. The first attempt got the login part right, but it missed some of the navigation logic I described. After tweaking the description to be more specific, it worked better, but I had to iterate a few times.
I’m wondering if others have had similar experiences. Does the AI copilot get it right on the first try for simpler tasks? And for more complex workflows with conditional logic or error handling, how much manual intervention do you typically need? I’m trying to figure out if this approach actually saves time compared to building it myself or if it’s just shifting the work around.
I’ve found that the copilot works best when you’re specific about what you want. The key is treating your description like you’re talking to someone who’s never seen the website before.
Instead of saying “extract the price,” try “find the text that starts with a dollar sign in the product details section, then copy everything until the next line break.” That level of detail pays off.
For complex workflows, I usually generate the core automation and then test it. If something breaks, I adjust the description and regenerate just that part. It’s faster than coding from scratch, especially for multi-step workflows.
The real win is that you get a working baseline in minutes instead of hours. Then you can focus on edge cases rather than building the whole thing.