Cohort 9

Head of Product

Allison Varnes

Product managers who drive strategy, development, and launch of products.

Engineers and engineering leaders who build, deploy, and scale software systems.

Applying AI tools and techniques to professional workflows — assign alongside more specific AI topics.

Identifying opportunities and validating what to build through customer research, experimentation, and prioritization.

#1 Rated AI Certificate. Acquire the skills needed to confidently build AI products, positioning yourself for success in the AI world

Product Leader, Codex at OpenAI

Rohan Varma

Product Leader - Codex at OpenAI | Ex-Cursor's First PM. 

AI Product Management Certification  Plus Get 6 More Live Certifications FREE

Moe Ali, CEO @Product Faculty

Over the last decade, Product Faculty has trained 10,000+ product leaders at world class companies.

<h3>Why I enrolled</h3>
<p class="p2-tall">Level up and increase my value as a senior product leader with a credible certification that will give me the skills and confidence to navigate our rapidly evolving field of work. </p>
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    <h3>A breakthrough moment</h3><p class="p2-tall">My honest reflection so far is, firstly, I'm loving how much feels like a refresher on just good product management. As someone who hasn't jumped into the AI world with both feet yet and hasn't come from a technical background, it makes the shift feel a lot less intimidating than before I started the course. I'm finding the content energising rather than daunting and I'm hopeful that continues as I get more hands on. So, "aha" - I <strong>can</strong> do this. <br><br>Other takeaways: <br>- Start simple, don't aim for perfection and keep experimenting is even more important in AI product management than traditional. Particularly love this as a former founder used to the "move fast, break things" approach. </p><p class="p2-tall">- Keep pace with the latest models and releases. You can't rest on your laurels. Model selection isn't permanent, if anything you should keep questioning whether it's the right one and not hesitate to experiment with another. </p><p class="p2-tall">- Avoiding inflated stakeholder expectations is arguably even more of a challenge when it comes to AI features. I've already felt this in the last 12-18 months as the AI buzz has swelled and non-technical leaders in the business have become swept up in the promise of it's magic. Being the pragmatic one to bring them down to earth makes you something of the fun police so balancing it with results is even more important to demonstrate proficiency and garner trust rather than lose it. </p><p class="p2-tall">- Top-of-mind areas I'm still a bit wary of and keen to feel more confident with: estimating token usage and safeguarding against abuse (e.g. prompt injection in multi-agent systems). </p>

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<h3>What I’ll apply</h3>
<p class="p2-tall">I'm excited to continue to play with the tools, refine my core stack and build. I want to explore more of the available models and tools to have a more confident grasp of the capabilities and get a better sense of what I prefer. I'll also enjoy feeling more part of the wave with a more confident comprehension level than an observer on the sidelines getting a little bamboozled because I'm not in the weeds which is how I felt before the course. </p>
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