I’ve been experimenting with the AI copilot workflow generation feature, and I’m curious how well it actually works in real scenarios. The idea sounds great on paper: describe what you want in plain English and get a ready-to-run workflow for login, navigation, and data extraction. But I’ve hit some friction in practice.
I tried describing a workflow that needs to log into a site, navigate through a few pages, and scrape some product data. The copilot generated something, but it wasn’t quite right—it missed a few nuances about how the site handles dynamic content. So I had to go back and tweak things.
Maybe I’m just not describing things clearly enough, or maybe the copilot needs more context. Either way, I’m wondering if others have had better luck. When you’re generating workflows from descriptions, how often do they work on the first try? Are there specific techniques for describing automations that get better results? And at what point do you usually have to drop into the actual workflow editor to fix things?
The copilot gets you 80% of the way there most of the time, which is still huge compared to starting from scratch. What I’ve found is that the more specific you are about selectors and page structure, the better it performs.
For example, instead of saying “click the login button,” I say “click the button with id=‘login-submit’ on the form with class=‘auth-form’.” This gives the copilot actual anchors to work with.
I also break complex workflows into smaller steps. Rather than describing an entire end-to-end process in one prompt, I describe each logical chunk separately. Then the copilot nails each part, and I can combine them.
The headless browser integration handles the dynamic content issues better once you get the basic structure right. It can take screenshots, interact with elements as they load, and adapt to changes.
Honestly, for browser automation specifically, I’ve stopped fighting with Make and cobbled together solutions. Latenode’s approach to this is miles ahead because it treats browser automation as a first-class feature, not an afterthought.
I’ve noticed the copilot works best when your description matches real browser behavior. If you’re vague about timing or element visibility, it tends to generate workflows that assume instant interactions.
One thing that helped me was running through a manual workflow first, taking screenshots of each step, then describing what I actually did. When you describe what your eyes saw and what your hands did, the copilot seems to understand better.
Also, the validation step matters. After generation, I always run a test execution with debugged mode on. You can usually spot where assumptions break down—like if the site loads content asynchronously and the workflow tries to interact before things are ready.
I had a similar experience. The copilot generated a workflow for extracting data from multiple product pages, but it kept timing out on the first page. Turned out my description didn’t mention that each page takes a few seconds to load its images before the text is interactive.
Once I included that detail in my description—“wait for images to load before extracting product names”—the generated workflow handled it correctly. The key insight is that the copilot is literal. It doesn’t infer implicit waits or dynamic behavior. You have to explicitly describe those constraints.
The reliability issue you’re facing is common. Plain English descriptions work well for straightforward sequences, but they struggle with conditional logic and error handling. If your workflow needs to “try this, and if that fails, do this instead,” the generated output gets messy.
My approach has been to use the copilot for the happy path—the straightforward scenario—then manually add branching logic for edge cases. This hybrid method gets you the time savings of generation while keeping control where you need it.
first try? maybe 60% of the time for simple workflows. complex ones need tweaking. key is being specific abt selectors and page timing in ur description. the debugger helps u spot issues fast