Who is this course for?

Product owners and product managers whose team is waiting to hear what an AI feature should do.

What do I leave with?

A brief a team can start from: the ask, what comes first, and the limit. A vague wish is not the outcome.

Is this the thirty-hour AI in Product Management course?

No. That course walks the whole product cycle. This one is the page the team builds from.

No. You need to decide the feature. The model does not get to invent the product.

Do you guarantee a job after a cohort?

No. We publish dates, prices, refund terms and consented stories. Placement and income claims are not part of this academy.

What time zone are live sessions in?

Source zone is America/Toronto unless a cohort says otherwise. Session times always name that zone. Convert in your own calendar from the ICS on the cohort card.

Can I join a waitlist if a cohort is full?

Yes. Waitlist captures name, email and optional phone. It does not take payment. Seats that free up are offered in join order.

How does early-bird pricing work?

If a cohort has an early-bird price and the cut-off has not passed (server date at payment), checkout charges the early-bird amount. The cart may still show list price until quote.

What is the refund window?

Full refund before the published cut-off relative to the cohort start; after that the published bands on the Refund page apply. Checkout requires you to accept that policy.

Product · NGS-1022

Generative AI for Product Owners

Your team is waiting to hear what the AI feature should do, and a vague wish will let them down. This course helps you write the ask, choose what comes first, and set the limits before anyone builds the wrong thing. You leave with a page they can trust.

12 hours
Practitioner
Live virtual
November 7 — November 21

Benefits

Documents your team can build from the next morning.
A way to describe an AI feature in plain product language.
A small test you can show a sponsor before the feature ships.
Customer research that still sounds like the customer.

Course overview

12hours

1
A PRD and stories a team can build
2
A roadmap you can defend
3
Research that stays the customer's words
4
Can we build this AI feature
5
How you will know it works
6
A human still owns the decision

The engineer will ask for the limit. The sponsor will ask for the promise. You are in the middle. This course is for product owners, product managers, and analysts moving into product. You do not have to pretend you write the code. You draft a brief and acceptance criteria a team can build from the next morning. You defend what comes first with evidence, not with a longer list. You keep the customer's words as the customer said them. You practice describing an AI feature in product language, including what it must never do on its own. The instructor reads the brief the way your team will. You leave able to show a small test before the feature ships, with the documents and 90 days of recordings. Three live weeks. Dates and the fee are on this page.

Outcomes

What you will be able to do when the course ends. This is not the list of things you take home. That list is Benefits, at the top of the page.

1You can draft a product brief a team can build from.
2You can defend what you will build first, with evidence, not volume.
3You can keep customer research in the customer's own words.
4You can say what the product must never do on its own.

Curriculum

Every chapter is listed here. You enrol in the whole course, not one chapter.

Module 1
A PRD and stories a team can build
Acceptance criteria, and the edge cases a model will invent if you do not write them.
- The PRDProblem, user, outcome, and what is out of scope. The model does not get to invent the product.
- Stories and the edge casesAcceptance criteria, and the cases a draft will skip if you do not name them.
Module 2
A roadmap you can defend
Priority from evidence, not from the loudest stakeholder.
- Evidence before volumeUsage, interviews, and the cost of waiting. Not the loudest stakeholder.
- A narrative a sponsor can repeatNow, next, and later — in one page.
Module 3
Research that stays the customer's words
Interviews and competitors, synthesized without smoothing out the conflict.
- Interviews without the smoothingKeep the conflict. A synthesis that deletes the disagreement is not research.
- Competitors, brieflyWhat they ship, who it is for, and the gap you will not pretend to close.
Module 4
Can we build this AI feature
Prompt, retrieval, or a finer model. The trade you are actually making.
- Prompt, retrieval, or a finer modelThe trade in product language: quality, cost, and what the user sees when it fails.
- A scope you can hand overThe job of the feature, the data it may see, and the job it must not take.
Module 5
How you will know it works
A small evaluation set before the feature ships.
- A small set before you shipExamples you already know the right answer to.
- A person still scores itWhat "good" means in your product, not in a vendor chart.
Module 6
A human still owns the decision
Escalation, and what the product must never do alone.
- EscalationWhen the product must stop and ask.
- What it must never do aloneThe line you write down before the feature is built.

Schedules for Generative AI for Product Owners

AIPO-2611

Generative AI for Product Owners

18 seats open

Shailesh Gabhane

Founder · Lead Trainer

English

Trainer profile

Where and when

Sat, Nov 7, 2026 — Sat, Nov 21, 2026
Saturdays · 10:00–14:00 ET
Zoom
Live virtual · Toronto

More details

$700 early bird

$595

Outcomes

You can draft a product brief a team can build from.You can defend what you will build first, with evidence, not volume.Live online12 hoursPost-course resources & support

Who can attend

Built for people like you

You will get the most from this ifProduct owners, product managers, business analysts moving into product

What to bringYou already write stories or a roadmap. Prompt & Context Engineering is useful, not required.

Instructor

Shailesh Gabhane

Founder · Lead Trainer

CBAP, PMP, CSPO

Delivery practitioner who built NGSB so working adults in the GTA could see a clear path into BA, PM and agile roles — without guessing the next step.

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Ready to become the product manager who directs AI instead of just using it?

FAQ’s

Who is this course for?: Product owners and product managers whose team is waiting to hear what an AI feature should do.
What do I leave with?: A brief a team can start from: the ask, what comes first, and the limit. A vague wish is not the outcome.
Is this the thirty-hour AI in Product Management course?: No. That course walks the whole product cycle. This one is the page the team builds from.
Do I need to code?: No. You need to decide the feature. The model does not get to invent the product.
Do you guarantee a job after a cohort?: No. We publish dates, prices, refund terms and consented stories. Placement and income claims are not part of this academy.
What time zone are live sessions in?: Source zone is America/Toronto unless a cohort says otherwise. Session times always name that zone. Convert in your own calendar from the ICS on the cohort card.
Can I join a waitlist if a cohort is full?: Yes. Waitlist captures name, email and optional phone. It does not take payment. Seats that free up are offered in join order.
How does early-bird pricing work?: If a cohort has an early-bird price and the cut-off has not passed (server date at payment), checkout charges the early-bird amount. The cart may still show list price until quote.
What is the refund window?: Full refund before the published cut-off relative to the cohort start; after that the published bands on the Refund page apply. Checkout requires you to accept that policy.

Generative AI for Product Owners

Benefits

Course overview

Outcomes

Curriculum

Schedules for Generative AI for Product Owners

Generative AI for Product Owners

Built for people like you

Shailesh Gabhane

Ask a question

Reviews

Ready to become the product manager who directs AI instead of just using it?

FAQ’s

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