Amazon

Canva

Esade

Dentsu

Harvard Business Review

GK & Jason

Built by ex-Amazon: ML PM & an ex-VP | Lenny Featured Lightning Lesson

Cohort 1

pm-moat-cohort-1

workshop-1

What you'll learn<ul><li>What "becoming technical" means.&nbsp;You must write structured logic engineers can test against</li><li>Live demo of a system.md that translates a PRD.&nbsp;Show how the AI thinks, using the Working Backwards approach</li><li>evals.md created with multi-dimensional thresholds.&nbsp;With binary criteria, through a Bar Raiser's lens</li><li>Q&amp;A&nbsp;(we answered a lot of questions)</li></ul>

Raise Your Technical Bar as an AI-Native PM (63min Lightning Lesson)

What you'll learn<ul><li>What "becoming technical" means. You must write structured logic engineers can test against</li><li>Live demo of a system.md that translates a PRD. Show how the AI thinks, using the Working Backwards approach</li><li>evals.md created with multi-dimensional thresholds. With binary criteria, through a Bar Raiser's lens</li><li>Q&amp;A (we answered a lot of questions)</li></ul>

Defining your moat through four key pillars as an AI-native PM and raising your technical bar in the process

ex-Amazon Sr. PM, running 3 ventures

Typeform

Chargebee

Zoho

GK Shan

Product & AI Consultant, ex-Amazon Sr PM (ML), currently running three ventures

Co-Founder, Level Up; $1B+ P&L; led 40+

IPG Mediabrands

Techstars

Jason P. Yoong

Co-Founder & COO at Level Up (fmr Amazon, VP at Dentsu, Startup - $8M seed)

Over 15,000 product professionals signed up for our <a target="_blank" rel="noopener noreferrer nofollow" href="https://maven.com/p/b062b8/raise-your-technical-bar-as-an-ai-native-pm">Lightning Lesson.</a> 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<ul><li>embed your moat into artifacts: specs, constraints, decision criteria, evaluation logic, and workflows that engineering can build from.</li><li>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.</li><li>vibe-coded these on Claude Code (or equivalent), with no technical background</li></ul>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.

Orgs are busy investing in AI infra. Make it hard for them to ignore your value

ENCODE: Turn your knowledge into specs that engg builds from

BUILD: Embed your moat in Claude Code, with no prior coding knowledge

DEPLOY: Walk into any discussion with the right specs

COMPOUND: Incrementally improve your moat and benefit from model upgrades

Shift from mainstream PM trends and updates

Every session runs inside an AI coding tool. Claude Code or Cursor are recommended. Install before Session 1 and enable file access.

Claude Code or Cursor installed on your laptop

A paid plan (Claude Pro/Max or Cursor Pro)  is required before Session 1 for you to test and play with the demo.

Pro (or higher) plan for your chosen tool

You'll build artifacts from your own context. Leadership reviews, problem scenarios, specs, planning docs, or a Notion/Drive export.

Have example  product docs, problems and data you can work with

<pre><code class="language-markdown">Roles: Product Managers, Product Leads, Principal PM, Director of Product, Group PM, Product Designers</code></pre>

<pre><code class="language-markdown">Experience: 3–10 years in product; at least 2 years shipping features for a real customer base</code></pre>

<pre><code class="language-markdown">Company type: Mid+, scale-up, or enterprise with an active AI product roadmap, not a solo founder or pre-product startup</code></pre>

PMs and engineers are merging into builders. Vibe coding only gets you halfway.

Gayathri Keerthana (GK)

AI Consultant, ex-Amazon SrPM (Machine Learning), 3x Founder

You're likely already facing this: vibe-coded prototypes break before a real customer can use them. 15,000+ professionals came for my Lenny-featured Lightning Lesson where I showed a primer to fix this.There's a new role forming in every product team - Product Builder - someone who can ship in short sprints with the customer at the center.The real question is how to engineer a build that holds past mid-build, without wasting millions of tokens on vague vibe-coding.Spec Engineering fixes this. Anthropic has been publishing on this but hardly anybody talks about it or shows how it will look like in your world.In this workshop, I'll show you how to do a spec-driven build on a real problem:🧩 Plan: Working Backwards into a spec the harness can build from.🤖 Build: lock "done" as a Bar Raiser commit, build one feature at a time with handoffs that survive context resets.🔍 Evaluate: a sperate agent that catches what self-grading misses, calibrated to your quality bar🔁 Strip: remove scaffolding as the model improvesSo what: I show harness design encoded with first principles. I've used these at Amazon scale. They outlast model upgrades. Scroll down to testimonials for the rest.

Walk out as a Product Builder, closing the loop from customer problem to shipped agentic build.

You leave knowing how to run spec-driven builds, even if harness is new to you

You leave with a spec your harness can build from

You ship a build that works past the demo & into your team's workflows

You set up an independent eval calibrated to your taste, not the model's settin

You learn the strip habit that makes your harness survive model upgrades

You walk out as a Product Builder

Claude Code, Cursor or equivalent installed 

bring an idea for an internal tool you'd actually use (e.g., a custom builder pulling from your own data sources)

A small tool or app you want to build

PMs who are becoming builders, coding fluency doesn't matter

Engineers who want to wear the PM hat, build customer centered products

Vibe-coders who want to build products that don't crumble mid-build and make the token burn worth it

Raise the bar for your AI PM workflows. Live on Claude Code.

Product & AI Consultant, ex-Amazon Sr PM (ML), running 3 ventures

Most PMs are wondering "how to stay relevant in the AI-PM race."This is what we learned from over 15,000 product professionals who signed up for our <a target="_blank" rel="noopener noreferrer nofollow" href="https://maven.com/p/b062b8/raise-your-technical-bar-as-an-ai-native-pm">Lightning Lesson.</a>The real question for 2026 is how to go beyond PRDs and get closer to your leadership and engg teams.The answer is not prompt hacks or Claude tips, because they're not strategic enough to make your work look any different from the next PM's.In this 5h workshop, we teach how to produce AI PM artifacts using first principles:🔁 Working Backwards from customer problem to a product spec that engineering can directly build from. Then encode it into your CLAUDE.md so that your AI is context aware every session.🔍 Deep dive orchestrators that navigate fuzzy data and find real root causes. You save the day and present it right.📐Bar Raiser workflows that raise the quality of every AI output, from product specs to QBRs.🎯Agents that use the "8-persuasion factors", before any leadership review.We have seen these principles help scale startups and billion dollar orgs. We see what AI-enabled products are missing today.We will show you how to encode them in artifacts and agents using Claude Code.

Raise your bar as an AI-native product leader

Close the gap between product and engg

Become the Bar Raiser PM that defies AI slop

 You stop re-explaining context to your AI. Control token burn and hallucination

Finding the real root-cause and making it visible

LLM concepts underneath each framework

Every session runs inside Claude. Install Claude Code or Cursor before Session 1. A paid plan (Claude Pro/Max or Cursor Pro) is required.

Claude Code or Cursor installed on your computer

You'll build artifacts from your own context. Leadership reviews, problem scenarios, specs, planning docs, or a Notion/Drive export.



Example product docs, problems, and data you can work with

<pre><code class="language-markdown">Product People - anybody who wears the Product hat (not just PMs), want to raise their technical and quality bar. </code></pre>

<pre><code class="language-markdown">3–10 years in product or engineering; at least 2 years shipping features for a real customer base</code></pre>

<pre><code class="language-markdown">Mid-size, scale-up, or enterprise with an active AI product roadmap</code></pre>

Vibe-coding the Agent Owner Spec: 
for AI-native PMs

AI and Product Consultant | ex-Amazon Product Leader | ESADE MBA

Co-Founder & COO at Level Up (Prev: Amazon, Dentsu, IPG, Startup - $8M seed)

Learn from catastrophic agent deployments through the lens of One-way / Two-way door decisions

How to recognize and pre-empt failure patterns

Post-mortems trace every major AI failure to one question: who defined what the agent was allowed to do?

How you tackle this being the Agent Owner for your org

We vibe-code an Agent Owner spec in Claude Code. Watch what it can do, what it pre-empts and what failure looks like.

Live demo: Build the Agent Owner spec

Spec Engineering: the Unclaimed Role of an AI-native PM

What changed about the spec and how the gap looks like in your org

Learn why the old PM spec doesn't translate to AI agents

The industry named the highest-leverage skill in AI development "specification engineering." Learn how to claim it.

Understand why Spec Engineering is a PM skill

Take home a structured spec template using a Working Backwards approach that you apply in your next spec engg exercise

GK & Jason will help you become a Bar Raiser AI PM

GK & Jason

About Level Up With AI

Courses

Build Your Moat as an AI-native PM - Practitioner Certificate

Workshops

The Product Builder Certification: From Vibe Coding to Spec Engineering

AI PM Certification: From Specs & Evals to Leadership Sign-off

Lightning Lessons

Vibe-coding the Agent Owner Spec: for AI-native PMs

Spec Engineering: the Unclaimed Role of an AI-native PM

Resources

Raise Your Technical Bar as an AI-Native PM (63min Lightning Lesson)

Raise Your Technical Bar as an AI-Native PM (63min Lightning Lesson)