ex-Amazon Sr. PM, running 3 ventures
Co-Founder, Level Up; $1B+ P&L; led 40+


Over 15,000 product professionals signed up for our Lightning Lesson. We intuitively knew what AI-native PMs want.
You have watched customers misuse features, seen promising ideas collapse during rollout, and sat through NPS reviews, and stakeholder debates You know where product works and where it fails.
This your moat.
The reality is that customers never meet the model in the abstract. They meet the product experience it shapes.
The gap between a technically capable product and one that earns trust is almost always a specification problem. Your moat forms when your judgment becomes usable inside AI-assisted product work.
This course helps you
embed your moat into artifacts: specs, constraints, decision criteria, evaluation logic, and workflows that engineering can build from.
apply principles that GK (as an ML PM) and Jason (as a COO) have seen work at scale, such as Working Backwards, 5-Whys, and Bar Raiser approaches.
vibe-coded these on Claude Code (or equivalent), with no technical background
The PMs with the strongest long-term advantage will be the ones who can encode judgment with precision, raise the quality bar for outputs, and make their reasoning legible across teams.
Defining your moat through four key pillars as an AI-native PM and raising your technical bar in the process
Map customer tripwires, product logic, stakeholder reviews and business constraints into specs that engg directly builds from
Leave with CLAUDE.md and system.md set up: the foundation and map your AI systems follow.
Working Backwards, Deep Dive, Bar Raiser (proven at $1B+ scale), rebuilt as Claude Code workflows in every live session.
Leave with evals, agentic systems that assist you with root cause analyses, briefs, pressure-testing, multi-dimensional rubrics
Test your new PM toolkit and track your AI product's performance through observability metrics
Develop Leadership Briefs that distill your RCAs & recommendations
Leave with meta-prompts and skill files that will help you compound the value of your moat and scale as new AI models arrive
Gain a deeper capability: making your judgment legible, transferable, and usable inside AI-assisted PM workflows
Every session runs inside an AI coding tool. Claude Code or Cursor are recommended. Install before Session 1 and enable file access.
A paid plan (Claude Pro/Max or Cursor Pro) is required before Session 1 for you to test and play with the demo.
You'll build artifacts from your own context. Leadership reviews, problem scenarios, specs, planning docs, or a Notion/Drive export.
Live sessions
Learn directly from GK Shan & Jason P. Yoong in a real-time, interactive format.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Lifetime access
Go back to course content and recordings whenever you need to.
Office hour
1.5 hours of live OH with GK and Jason
Community of peers
Stay accountable and share insights with like-minded professionals.
Hands-on projects
Take home assignments and closing the loop on live Q&A sessions
Maven Guarantee
This course is backed by the Maven Guarantee. Students are eligible for a full refund up until the halfway point of the course.
5 live sessions • 7 lessons • 3 projects
Apr
28
From Customer Failure to Shippable Spec
Apr
30
Live Demo: From Business Problem to Root Cause using Agents
May
5
How Leaders Decide When the Data Runs Out — Live with Jason Yoong
May
7
Live Demo: Run every persuasion layer on your AI-output

What you'll learn
Live sessions
3-4 hrs / week
Tue, Apr 28
5:30 PM—6:30 PM (UTC)
Thu, Apr 30
5:30 PM—6:30 PM (UTC)
Tue, May 5
5:30 PM—6:45 PM (UTC)
Projects
1-3 hrs / week
Async content
1 hr / week
GK was excellent to work with. She supported us across AI workshops and AI course tutoring, and consistently delivered high-quality, well-structured materials and outputs. Communication was clear and proactive, and she genuinely cared about achieving strong outcomes, not just “completing tasks.” She also interacted brilliantly with students and workshop participants: engaging, supportive, and very clear in explanations and facilitation. Everything was delivered on time, with strong attention to detail, and she stayed flexible and responsive as priorities and timelines evolved[...]she’s thoughtful, reliable, and simply a great person to collaborate with. I strongly recommend her for training delivery/support and for helping early-stage startups, especially across AI, marketing, and product

Vitaly
We were seeking a product owner who was able to translate the rather abstract concept of [a model idea] into a product that is valuable to the larger business unit. They had to help us understand how the ML model can be leveraged to solve concrete business problems and surface actionable insights for business users. This is where Gayathri shone. She laid out and executed a strategy for business application… She orchestrated the document with simple and easy-to-understand language and used relatable examples… Gayathri's contributions have not only advanced the team's understanding of customer behavior but have also set new benchmarks for how we leverage machine learning in business.

Principal Applied Scientist
In my 10 years of product experience in the technology sector, working with PMs from the US and Europe, I've not seen a lot of young leaders exhibiting the same level of innovation, leadership, and problem-solving that GK consistently demonstrates… She exemplified 'Invent and Simplify' by creating an override mechanism… GK has proven herself to be an innovative leader in a large organization while driving technological solutions growth from start to finish… Her customer obsession, innovative problem-solving abilities, and potential to develop scalable solutions make her an exceptional candidate.

Sarah
I have not come across many such product leaders in my 14 years of experience in tech and product management, including a decade at Amazon… Her strategy was validated when the findings from the econometric model aligned with the insights from the ML model. That's when I witnessed that she has the acumen to integrate different methodologies into a cohesive strategy… She transformed raw ML outputs into a user-friendly interface that allowed non-technical users to extract predictions on demand impact… She consistently pushed the operations teams to look beyond immediate hurdles and focus on broader customer behavior trends… Her entrepreneurial spirit, customer obsession, and innovative problem-solving skills will undoubtedly enable her to continue making significant contributions

Shiv
She set a precedent amidst several retail orgs by successfully applying advanced econometric model outcomes to practical product features that delight customers. She takes a bold and innovative approach to strategic decision-making to live testing… She led this at a time when the team was facing a centralized funding freeze and managed to secure sponsorship from senior leadership… From an external research team standpoint, GK's execution helped us get a full picture of connecting customer needs to product solutions and commit to innovation — which is challenging to achieve in a large organization

Tom








$1,300
USD