The AI Copilot: Our First 30 Days

We launched the copilot with one job: turn a plain-English description of a workflow into a working pipeline with nodes, retries, and alerts. Thirty days in, that's exactly what it does — with two honest caveats.

What it nails

• First draft: describe an onboarding flow in a paragraph, get a passable pipeline in seconds.
• Naming: it generates human-readable step names, which make the builder dramatically easier to keep clean.
• Error explanations: 'the webhook timed out because the payload exceeded 10MB' beats guessing.

Where it still needs you

The draft is a starting point, not the finish line. It optimizes for the described happy path, so edge cases — 'what if the customer is already in the CRM?' — still want human eyes. That's by design: everything it writes lands in review before it can go live.

The human-in-the-loop loop

Sensitive steps (payments, data deletion, external sends) are gated behind an explicit approval. The copilot drafts, the human approves, the machine executes. That division of labor is the whole product thesis.