I keep seeing this marketing angle about describing your automation in plain English and getting a ready-to-run workflow spit out. But every tool that promises this seems to either give you something unusable or something so basic it could’ve taken two minutes to build manually.
I’m genuinely curious whether anyone here has gotten this to work. The specific thing I’m interested in is whether it can handle transformations—like, if I describe “I need to clean up user data by parsing JSON responses and filtering out duplicates,” does it actually generate the JavaScript transformation steps, or does it just create the basic structure and leave you hanging?
Because if it’s the latter, it’s not really saving time. You’d still be writing the actual logic yourself, which defeated the purpose.
Has anyone actually tried this with a workflow that includes custom code or data transformations? Did the generated code work on the first try, or did you end up rewriting most of it?
This is where AI Copilot Workflow Generation actually shines, not in the way you might expect from the marketing. It won’t generate perfect, production-ready code from vague descriptions. But it absolutely can generate a working skeleton that includes transformation steps.
I’ve used it for workflows with JavaScript steps included. You describe something like “parse this CSV data and transform it,” and it creates the workflow structure with a JavaScript node positioned exactly where you need it. From there, the AI assists you in writing the actual transformation logic.
So it’s not magic—you’re still involved—but it saves you from building the entire scaffold from scratch. That’s the real time saver. And because it understands context, the code suggestions it makes for those transformation steps are actually relevant to your use case.
The key difference from other tools is that this workflow generation isn’t separate from code generation. They work together. You get structure and logic in the same go.
See for yourself: https://latenode.com
I tested this thoroughly about four months ago because I was skeptical like you. The honest answer is nuanced.
The workflow structure generation is legitimately good. If you describe a multi-step process, it understands sequencing, ordering, and where different operations fit. That part actually works. Where it gets fuzzy is custom logic.
For basic transformations—simple filters, field extractions, straightforward JSON parsing—the generated code works. For anything more complex, you’re basically getting guidance. The AI suggests approaches but doesn’t generate bulletproof code.
What I found valuable was using it as a starting template. Five minutes of description saved me an hour of structural thinking. Then I spent an hour refining the actual logic. Without the generation, that would’ve been two hours total.
The reality is that workflow generation works best when you’re crystal clear about what you want. Vague descriptions produce vague workflows. But if you’re specific—“receive JSON from webhook, filter by date range, extract customer IDs, append to Google Sheet”—the generated structure is actually solid.
The transformation code quality depends on how well you’ve described the transformation. Simple, well-defined transformations often work without modification. Complex business logic usually needs adjustment. This isn’t a failure of the tool; it’s just how AI generation works right now.
Most efficient approach I’ve found: use it to generate the flow, manually review and refine any generated code, test against real data before deploying.
Workflow generation that includes transformation steps is genuinely useful, but calling it “write your workflow from English” oversells the capability. What’s actually happening is that the platform is inferring workflow structure from your description, which is legitimately hard and useful to have automated.
The transformation code generation is assistive, not automatic. Where it shines is in suggesting the right approach for common patterns. Where it struggles is with domain-specific or novel transformations.
If you evaluate this as “saves me from thinking about architecture,” it delivers. If you evaluate it as “no coding required,” it oversells. Position it correctly within your team and it’s a real productivity multiplier.
Yes, it works for structure and basic transforms. Expect to refine complex logic yourself. Be specific with descriptions for better results.
Good for scaffolding, not magic. Be specific. Review generated code.
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