Should AI run user onboarding unsupervised?
AI should draft user onboarding, not run it unsupervised. Models are good at turning your product, ICPs, and a user's answers into a structured sequence. They are bad at owning publish, policy, and taste. Dual-save keeps draft and live apart so nothing reaches a new user until you say so.
Should AI run user onboarding unsupervised?
AI should not run user onboarding unsupervised. Models can fill a structured path. A human still owns the live one. If the tool can publish without you, it is not drafting. It is deciding.
I built Krest around that line because I kept seeing the opposite pitch: set it and forget it, the agent will onboard everyone overnight. That is how you get generic copy, the wrong aha, and a tour that talks like a different company.
The locked sentence is simple. AI drafts. You ship. It is a boundary, not a slogan. Krest facts keeps that claim in the same words we use here.
What is dual-save?
Dual-save means draft and live are separate copies of the same path. You can rewrite a step without changing what a new user sees until you publish. If draft and live are the same object, you do not have a review step.
Undo is not dual-save. Undo rewinds one object after the damage. Dual-save keeps the experiment off the session. You can throw the draft away. Live stays what you last published. The activation glossary names dual-save the same way.
What is AI actually good at in onboarding?
AI is good at reading your product and proposing a first path. Paste a URL. It can structure USPs, name ICPs, and draft a sequence for an enterprise lead from a competitor or a manager of a team of 10. That is blank-canvas work you should not do by hand every time.
It is also good at a second pass: invite stalled for PMs, tighten that step. A suggestion you can apply or edit is useful. A silent rewrite of production is not. Read how that pairing works on Krest AI.
Why do AI onboarding drafts go generic?
Drafts go generic when the model has nothing true to cite. Product knowledge and form answers are the spine. Without them, the model invents your category. With them, the checklist, tour, and email can only have been written for that pairing.
This is the honesty test for any “AI onboarding” tool. If it cannot show you the source it cited, you will spend the time you saved fixing a path that does not sound like you.
What should you ask a tool before you let it draft?
Ask where product truth comes from, whether you can edit one step without rebuilding the stack, and whether it can publish without you. If it can publish alone, keep it off live users. If truth and editability are weak, you will spend the time you saved fixing a path that does not sound like you.
Publish, policy, and taste stay human. You decide whether the aha is right, whether the email is honest, and whether that tour should wait. Nothing ships until you say so.
How do you review an AI-drafted sequence this week?
You review an AI-drafted sequence this week by reading the named aha, checking the segment, and editing the step you would not sign. Then look at draft and live side by side before you publish.
If the tool cannot show you those two copies, you do not have a review step. Keep it off new users. User onboarding still runs on a person who owns the outcome. AI is how that person moves faster, not how they disappear.
Questions people ask
Should AI run onboarding without review?
No. AI can draft checklists, tours, emails, and whole sequences from product context. A human still reviews, edits, and publishes. Unsupervised live onboarding is how you ship noise with your logo on it. Publish, policy, and taste stay human on purpose.
What is dual-save?
Dual-save means draft and live are separate copies of the same path. You can iterate a step, apply a suggestion, or rewrite a line without changing what users see until you publish. If draft and live are the same object, you do not have a review step.
What can Krest AI actually draft?
Sequences composed of forms, checklists, tours, emails, and hints, grounded in what it learned from your URL, docs, ICPs, and how you sell. It can also suggest a next edit when a step stalls. You still decide what goes live.
Why do AI onboarding drafts go generic?
Drafts go generic when the model has nothing true to cite. Without product context and form answers, it invents your category. With both, the checklist, tour, and email can only have been written for that pairing of product and person.
What should you ask before you let a tool draft?
Ask where product truth comes from, whether you can edit one step without rebuilding the stack, and whether it can publish without you. If it can publish alone, keep it off live users. If truth and editability are weak, you will spend the time you saved fixing the path.
Is dual-save the same as undo?
No. Undo rewinds a single object. Dual-save keeps a draft copy next to the live path so users never see the experiment. You can throw the draft away. Live stays what you last published. If you only have undo, a bad publish already reached the session.