Most AI courses sell hype. A new V2 product management course sells the opposite: a clear-eyed look at when large language models actually help product work and when they are an expensive distraction. The course launched on July 15, 2025, priced at $99 with lifetime access to all updates.
The framing is useful. The course is built around a fictional startup called HealthXYZ and walks through the messy real-world application of AI across discovery, delivery, and operations.
What the course actually covers
The course is not a generic "AI for business" module. The lessons go deep on the parts of product work where LLMs change the daily grind: prompt engineering, customising model behaviour, building custom GPTs (also called Gems in Gemini or Projects in Claude), and using deep research tools to map market and competitive landscapes.
It also covers how to apply AI to qualitative data sources most product teams already have: user interviews, support tickets, product requirements documents, and team retrospectives. Frameworks like the Product Strategy Canvas and user story mapping get an AI-augmented treatment.
The ethics module is the part most courses skip. It is included here, alongside guidance on the difference between free and professional AI accounts. The argument is that many LLM disappointments come down to using the wrong model tier for the job.
The course includes eight hours of self-paced video modules, three live Q&A sessions during launch week, six custom GPTs, and a complete certificate.
The Scrum angle
For readers working in Scrum, the framing matters. The course treats AI not as a silver bullet but as a force multiplier for the existing ceremonies and artefacts. Backlog refinement with AI support, sprint reviews powered by AI-summarised metrics, and AI-assisted user story mapping are treated as enhancements, not replacements.
The promised V3 update takes the same approach and stretches it across the full product operating model: strategy, discovery, organisational design, and team topologies. Anyone who buys V2 now gets V3 at no extra cost.
Why it matters
Two things make this course different from the crowded AI-upskilling market. First, it is honest about where AI is overhyped. Too many "AI for product managers" courses assume the model is right and the user just needs prompting. This one starts from the assumption that the wrong model tier or the wrong framing is the most common failure mode. That is a useful inversion.
Second, the lifetime access model addresses a real problem. The product AI landscape moves fast. A course bought in 2025 will be partly outdated by 2027. Free updates through V3 remove the pressure to buy a new course every time the tooling shifts.
The trade-off is precision. This course assumes you already know product management fundamentals. It builds an AI layer on top of existing craft, not a replacement for it. That is the right call for experienced practitioners. It is the wrong call for anyone still developing core product skills.
For agile teams, the practical question is whether this course beats internal upskilling. The answer depends on team size and budget. For a single product manager, $99 is cheap. For a team of ten, the better move may be to buy one seat and run an internal lunch-and-learn using the course materials.
A worked example: a PM trying to apply AI to discovery
Say you are a product manager in a mid-sized SaaS company. You have 40 user interview transcripts on your laptop, a backlog of 200 support tickets, and a vague brief for a new feature. Most AI courses would tell you to paste the transcripts into ChatGPT and call it a day.
The V2 approach is different. Use deep research to map the market, AI-assisted tagging on the support tickets to find patterns, prompt-engineered summarisation on the interview transcripts to surface unmet needs, and a custom GPT tuned to ask three provocative follow-up questions at the end of every output. That is a workflow, not a prompt.
Who should care
| Audience | Verdict |
|---|---|
| Experienced product managers | Strong fit. AI fluency without the hype, built around real PM workflows. |
| Scrum teams looking to upskill | Good fit if the whole team goes through it together. Solo access works for individuals. |
| Beginners in product management | Not yet. Learn the fundamentals first. AI is a multiplier, not a foundation. |
| Organisations standardising AI processes | Worth it for the frameworks and the custom GPTs, especially if you want consistency across teams. |
Bottom line
For product managers who already know Scrum and want a serious AI layer on top, this course is worth the $99. The lifetime access is the real value. If you are new to product management, start with the foundational course first. AI fluency is wasted without the underlying craft.
Key takeaways
- The V2 course launched on July 15, 2025 at $99 with lifetime updates.
- It treats AI as a multiplier for existing Scrum and product work, not a replacement.
- V3 is planned and will be free for V2 buyers.
- The course is best suited for experienced PMs, not beginners.
Frequently asked questions
When did the V2 product management course launch?
It launched on July 15, 2025.
How much does the course cost?
$99, with lifetime access to all future updates, including V3.
Do I need prior AI knowledge?
The course assumes you know product management basics but starts AI content from the ground up. Some prompt engineering experience helps but is not required.
Will I get the V3 update for free?
Yes. All V2 buyers get free lifetime access to future versions, including the planned V3.