So I’ve been wrestling with this for months. Every time I’d try to describe what I needed in plain English and have it generate a workflow, I’d get something that looked right on the surface but broke the second a website changed its layout or there was any variation in the data.
Recently I started experimenting with being way more specific about what I’m describing. Instead of just saying “log in and scrape the table,” I’m being explicit about selectors, wait conditions, error handling. It’s weird because you’d think the AI would just figure that out, but it really doesn’t.
The other thing that changed for me was testing each step individually before linking them together. Sounds obvious, but I was trying to build these massive workflows and then wondering why they’d fail halfway through.
I’m curious though—for those of you who’ve had success converting descriptions into stable workflows, how detailed do you actually get with your descriptions? Are you basically re-writing what you’d code anyway, or have you found a sweet spot where it’s actually less work than traditional coding?
You’re on the right track with being specific. The thing is, what you’re describing is basically the workflow that Latenode’s AI Copilot does automatically. You write your description, and instead of guessing, it generates a visual workflow with all those selectors and conditions already mapped out.
The difference is you don’t have to manually tweak each piece. You describe what you need, the copilot generates it, and then you can see exactly what it did in the visual builder. If something’s off, you adjust it visually instead of rewriting code.
I’ve found it cuts the “description to working workflow” time from hours to minutes. And when a site changes its layout, you can see the broken step immediately in the builder and fix just that part.
Yeah, the description-to-code problem is real. I spent a lot of time trying to make descriptions work for complex flows, and honestly what made the difference was treating the description as a spec document rather than casual instructions.
I’d outline:
Exact page selectors or identifiers
What counts as success at each step
What happens if something fails
Data extraction format
It’s more work upfront, but it prevents that nightmare of a workflow that runs but produces garbage data. The granularity matters way more than I thought it would.
One thing that helped me was realizing descriptions work best when you’re not trying to be clever. Skip the natural language tricks. Just say exactly what element you’re clicking, what text you’re looking for, what the output should look like. It feels robotic, but it actually translates way better to something executable.
I’ve seen this exact issue where descriptions generate workflows that work once then immediately fail. The root cause is usually that descriptions don’t capture the brittle parts—those edge cases and conditional logic that only matter sometimes. There’s a gap between what sounds good when you say it and what actually needs to happen in code. Testing individual steps is crucial, but also you need to document failure modes explicitly in your description, not just the happy path.
The stability issue comes down to how descriptive your descriptions actually are. Natural language is inherently ambiguous. “Click the login button” works when there’s one button, but breaks with multiple buttons or dynamic rendering. I’ve had better results when I treat descriptions like technical specifications—including CSS selectors, timing requirements, and data structure expectations. It’s more effort than casual description, but the workflows are significantly more reliable.
found that adding error conditions to descriptions helps alot. instead of just what u want to happen, say what shud happen if it fails. makes the generated workflow way more robust.