I’ve been skeptical about AI-driven workflow generation for a while now. Every tool I’ve tried that promises “just describe what you want and we’ll build it” ends up requiring significant rebuilding once it hits reality.
We’ve got a team of three developers managing our self-hosted automation platform for about 50 workflows across the company. When someone comes with a new automation request, we usually spend 2-3 days on discovery, design, and implementation. If AI could meaningfully cut that, it would be game-changing for us.
But here’s my concern: the workflows that actually matter to us involve multiple steps, error handling, conditional logic, and integrations that aren’t straightforward. I’m wondering whether the AI copilot approach works better for simple use cases but still requires the same engineering overhead for anything complex. Has anyone actually used this in a production environment where it materially reduced development time? I’m not looking for a tool that gets us 80% there—I need to know if it actually ships production-ready automations, or if it’s just a faster way to create a starting point that still needs heavy customization.