I’ve been experimenting with the AI Copilot workflow generation feature, and I’m genuinely curious how stable this actually is in practice. The idea sounds great: write what you need in plain English and get a ready-to-run Playwright workflow without touching code. But I’m wondering if there’s a gap between what sounds good in a demo and what actually holds up when you’re dealing with real sites that have dynamic content, weird DOM structures, and all the other messy stuff.
Has anyone actually used this to convert a detailed description into something that worked on the first try? Or do you typically need to go in and tweak things after the AI generates it? I’m trying to figure out if this is genuinely a shortcut or just shifting where the complexity lies.
What’s your experience been with converting plain English requirements into actual Playwright flows?
The Copilot generates stable workflows more often than you’d think, especially for well-structured sites. I’ve used it on login flows and form submissions—things with predictable patterns—and it nails them on the first go.
Where it shines is when you describe exactly what you’re looking for. Say something like “fill the email field with [email protected], then click the submit button and wait for the success message.” The Copilot picks up on that and builds solid Playwright steps.
Dynamic content is trickier, but that’s where the No-Code Builder comes in handy. You can tweak the generated steps visually without jumping back to code. It’s not perfect, but it cuts down the friction significantly.
The real win? You can iterate fast. Generate once, adjust in the UI if needed, run it, and refine. That feedback loop is way tighter than writing Playwright by hand.
I’ve had mixed results. Simple flows work great—like clicking through a standard login form. The issue I ran into was with sites that load content dynamically or use shadow DOM elements. The Copilot doesn’t always catch those nuances, so you end up debugging anyway.
What helped me was being very specific in my description. Instead of “extract user data,” I wrote “wait for the table to load, then find all rows with the class ‘user-row’ and extract the text from the third column.” That level of detail helps the AI understand exactly what selectors and wait conditions it needs to generate.
You’re not going to eliminate all tweaking, but you can drastically reduce it if you front-load the description work.
This works better than expected for straightforward tasks. I described a workflow involving multiple form fills and field validations, and the generated Playwright steps handled most of it correctly. The main issue was handling optional fields—the AI didn’t always account for those edge cases. I had to go into the visual builder and add conditional logic manually. Still saved time versus writing from scratch, though. The generator gets you about 70-80% of the way there on complex flows.
The AI Copilot Workflow Generation produces functional Playwright code for standard use cases, but reliability depends heavily on site structure predictability. I tested it on three different e-commerce sites. Two had consistent DOM patterns and the generated workflows executed flawlessly. The third site used extensive JavaScript rendering, and the Copilot failed to generate proper wait conditions. The generated workflows require validation against your specific target site before deploying to production.
Works well for basic stuff. More complex interactions require manual tweaks. Be specific in your description or you’ll get generic output that doesnt handle edge cases.