How to review an AI onboarding draft
You review an AI onboarding draft by opening it as two segments, signing the named aha, and keeping dual-save off new users until a person publishes. Read the product tour, checklist, and email as one path. Reject a step that could have been written for any product. AI drafts. You ship. The review is the publish gate, not a courtesy pass.
How do you review an AI onboarding draft?
You review an AI onboarding draft by opening it as two segments, signing the named aha, and keeping dual-save off new users until a person publishes.
Should AI run user onboarding unsupervised owns the should-question. How to automate user onboarding owns the draft loop. This page is the review pass between those two. The locked line stays the same. AI drafts. You ship. Krest facts keeps that claim in identical words.
What should you read first in an AI onboarding draft?
You should read the aha sentence first. If two teammates cannot say the stay in one verb, do not inspect hotspots yet.
A product tour written before that sentence is a feature list with a model behind it. What is an aha moment owns the definition of the stay. This page owns the order: sentence, then objects. How to write onboarding copy first is the same order when a person starts from a blank page.
Why open the draft as two segments?
You open the draft as two segments because an enterprise lead from a competitor and a manager of a team of 10 cannot share a first hour.
If both people get the same product tour and checklist, the model wrote an average path. A first name in a tooltip is not a review. Sign two paths or send the draft back. User onboarding is still one job per person: the path to the moment they stay.
How do you know an AI onboarding draft is generic?
An AI onboarding draft is generic when a step could have been written for any product. Invite the team, explore the dashboard, and click Next are the usual tells.
Product context and the answers the form already collected should make the line specific. If you cannot point at what the model cited, rewrite the step. Krest AI can propose the path. It is not the publisher. A generic checklist with your logo is still generic.
What is dual-save doing during a draft review?
Dual-save keeps draft and live as separate copies of the same path while you review. You can cut a step or throw the draft away without changing what a new user sees.
Undo is not dual-save. Undo rewinds after the session already took the hit. If the tool cannot show you both copies, keep the draft off live users. The sequence that is live stays what you last published.
What should you do with an AI onboarding draft on Monday?
Open today's draft as an enterprise lead from a competitor and as a manager of a team of 10, then publish only the path you would sign.
Write the aha each person is supposed to reach. Read the product tour, checklist, and email against that sentence. Cut the line that could live on a feature list. Look at draft and live side by side. Leave live alone if you would not sign. The activation guide is the longer map this review sits on.
How to review an AI onboarding draft before it goes live
- Write the aha the draft claims in one sentence a new user would recognize.
- Open the same draft as an enterprise lead from a competitor and as a manager of a team of 10.
- Read the product tour, checklist, and email as one path for each person.
- Cut or rewrite any step that could have been written for any product.
- Confirm dual-save leaves live unchanged, then publish only after a person signs.
Questions people ask
How do you review an AI onboarding draft?
You review an AI onboarding draft by opening it as two segments, signing the named aha, and keeping dual-save off new users until a person publishes. Read the product tour, checklist, and email as one path, not three widgets. Reject a step that could sit on any product. If draft and live are the same object, you do not have a review. The locked line is AI drafts. You ship. The review is the ship.
What should you read first in an AI onboarding draft?
Read the aha sentence first. If two teammates cannot say the stay in one verb, do not inspect hotspots yet. A product tour that walks chrome before the sentence exists is a feature list with a model behind it. Write the sentence a new user would recognize. Then read the checklist and email against that sentence. The aha post owns what the moment is. This page owns the order of the review.
Why open the draft as two segments?
You open the draft as two segments because an enterprise lead from a competitor and a manager of a team of 10 cannot share a first hour. If both people get the same product tour and checklist, the model wrote an average path. Personalization without two first hours is a first name in a tooltip. The review fails when the hour does not change. Sign two paths or send the draft back.
How do you know an AI onboarding draft is generic?
An AI onboarding draft is generic when a step could have been written for any product. Invite the team, explore the dashboard, and click Next are the usual tells. Product context and form answers should make the line specific to what you sell and who answered. If you cannot point at the source the model cited, rewrite the step. A generic path with your logo is still generic.
What is dual-save doing during a draft review?
Dual-save keeps draft and live as separate copies of the same path while you review. You can cut a step, apply a suggestion, or throw the draft away without changing what a new user sees. Undo is not dual-save. Undo rewinds after the session already took the hit. If the tool cannot show you both copies, keep the draft off live users. Publish is a human action.
What should you do with an AI onboarding draft on Monday?
Open today's draft as an enterprise lead from a competitor and as a manager of a team of 10. Write the aha each person is supposed to reach. Read the product tour, checklist, and email against that sentence. Cut the line that could live on a feature list. Look at draft and live side by side. Publish only the path you would sign. Leave live alone if you would not.