Vinoo Ganesh

Build Products Like a Forward Deployed Engineer

Palantir

Citadel

CEO, Kepler, Ex-FDE Lead at Palantir & Citadel | Built Frontline @ Palantir

The instinct you only develop by being in the room when things break.

Build from real customer pain

A concrete week-by-week playbook for customer calls, shadowing support, and building feedback loops.

Develop customer instinct from the field.

Why teams overbuild things nobody asked for or underbuild things that collapse.

Avoid the two mistakes that kill products

Walk away with the core skills, tools, and support you need to operate like a modern PM

18+ YoE | 8+ Yrs Teaching | 5K Students 

Linktree

Kajabi

Expedia Group

Harvard University

Melbourne Business School

David Wang (Product Dave)

Global Product Leader with 18+ Years of Experience from Hyper-Growth Companies

This cohort is designed for students who are based in Australia and the US West Coast timezones

Cohort 12PM AEST / 7PM PST 

Cohort 2 March 2026

AI has made building and execution dramatically easier. In 2024, the ratio of PMs to Engineers was 5 to 1 PM; in 2026, it'll be 1 Engineer to 2 PM.As AI professor <a target="_blank" rel="noopener noreferrer nofollow" href="https://en.wikipedia.org/wiki/Andrew_Ng">Andrew Ng</a> has pointed out, the biggest bottleneck in modern engineering teams is no longer coding — it’s product decision-making. <a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/posts/andrewyng_grok-raises-questions-meta-poaches-talent-activity-7351623555542896640-cTJT/">(</a><a target="_blank" rel="noopener noreferrer nofollow" href="https://www.youtube.com/watch?v=RNJCfif1dPY&amp;t=1105s">see the talk here</a><a target="_blank" rel="noopener noreferrer nofollow" href="https://www.linkedin.com/posts/andrewyng_grok-raises-questions-meta-poaches-talent-activity-7351623555542896640-cTJT/">)</a>Product decision making is deciding what to build, why it matters, and achieving business outcomes.This course gives you the foundation in a simple, no-fluff format with AI. You’ll learn how to prompt the AI to break down ideas, tie them to business metrics, AI for user research, define personas and JTBD, structure PRDs, and influence without direct authority.What You Get:<ul><li>A real product project you build and launch with AI</li><li>Weekly live workshops with hands-on practice so you build real skills fast.</li><li>1:1 coaching and feedback on your prompts, documents, and project.</li><li>A complete Miro board of PM tools — personas, segmentation, feature maps, prioritisation, roadmapping.</li><li>Practical AI prompt library used by PMs day to day to speed up every step of product work.</li><li>Career Happiness Refund: If you're not happy about the course, you'll get 100% refund anytime. (Btw, no one has done this yet)</li></ul>

Decide What To Build, Get Customers, and Drive Outcomes with AI PM Skills

Master the foundations of Product Thinking

Ground Product Decisions in Business and Customer Needs

Implement Data-Driven Prioritization and Planning

Translate Ideas into Clear, Actionable Product Requirements

Develop and Communicate a Complete Product Strategy

Product thinking needs real workplace judgement. This course promotes learning from each other's real-life experiences. 

Must be a Mid-Career Professional | 4+ Years of WORKING experience

We use real examples from tech companies and tech products; otherwise, you'll get lost in the concepts.

Must work in tech or tech-related products

Unofficial PMs - Engineers, Designers, Program Managers, BAs, and SalesFolks who touches product work and wants to define WHAT to build

New or Aspiring PMsPeople moving into PM who want practical product thinking, AI workflows, and a real project to show their ability.

PMs who needs to stay relevant in the AI eraCurrent PMs who want to remove low-level work and use AI to operate with more impact.

Using AI in product management is not just about getting better at ChatGPT. It's about how to leverage AI across the product development life cycle (PDLC) to accelerate, expand, and simplify what's possible. Unfortunately, most AI courses for PMs focus on how to build AI-powered features. But PMs can benefit from AI practices regardless of the type of product they are building. This is the focus of this course: helping PMs expand the daily practice of product management and giving PMs super powers. Over two weeks, you’ll learn—by doing—how to use AI to accelerate discovery, synthesize insights, explore solutions, and support decisions, while understanding where AI helps and where it can mislead. This is a hands-on, instructor-led cohort for PMs who make real product decisions. Course Structure (PDLC-Aligned):1.	Discover – AI-Accelerated Customer Discovery2.	Define – Insight Generation &amp; Problem Framing3.	Design – Ideation &amp; Solution Shaping with AI4.	Drive – Validation of Solutions, Decision-Making, Risk &amp; Trust Each session builds on the previous one with hands-on exercises on a real product idea. You practice using AI tools and refining your prompts while developing a critical mindset for when and how AI makes sense. How the Course Works: Duration: 2 weeks (short, intensive, focused) + Graduation Demo dayFormat: Instructor-led cohort with 4 live sessions (you get help as you go)Sessions: 2 sessions per week (gives you time to internalize)Between sessions: Hands-on individual assignments (to build the practical muscles) You will:•	Work on a shared real-life product case in small groups•	Complete individual exercises for each phase of the PDLC•	Review and discuss peers’ work•	Learn through comparison, challenge, and reflection•	Group collaboration is encouraged, but individual practice is required. Instructor:•	Author of "AI for Product Managers"•	Product leader with hands-on experience applying AI to real product work•	Focused on practical frameworks, not theoretical AI•	10-year experience running cohort-based training sessions for Product Managers This course is grounded in real-world product decision-making.

Get AI super powers to grow in your PM job

Course syllabus

Interactive sessions with the instructor to learn new topics, review assignments, and get support.

Tuesdays & Fridays

After each session, you work on a real product using the AI tools and practices learned in the session. This builds the muscles and your repeatable workflow.

Hands-on Assignments

At the end of the course, we'll meet for a final demo of the products built by each team and to get additional support.

Graduation Demo Day

Course schedule

Product Managers, Senior PMs, Group PMs. Product Leaders responsible for discovery and decision-making.

PMs who want to move beyond “AI curiosity” to real, practical capability. PMs who want hands-on practice to accelerate their own product job

This course is not a beginner introduction to product management or a tutorial on ChatGPT. It's a deep-dive on how to use AI in product work

Who is this course for

What you’ll get out of this course

Understand how AI expands each of the PDLC phases in Discovery, Define, Design, and Drive. Accelerate your process from problem definition to idea validation and drive innovation.

Accelerate your Product Management job

Learn how to use AI for customer and market Discovery, from creating synthetic users and interview guides, to conducting customer interviews. All with a critical eye focused on strategy.

Use AI to accelerate customer discovery without losing skepticism or empathy

Learn how AI can accelerate and expand insight generation, interview synthesis, and problem definition. Define problems without inventing false certainty.

Apply AI to synthesize insights and frame problems without inventing certainty

In the Design and Drive phases, AI can accelerate and expand ideation and problem-solution fit. Learn how to use AI to ideate, prototype, and validate new ideas quickly.

Use AI to expand solution space and prototype quickly, without premature convergence

Practice real-life product decisions while working hands-on with AI tools. Learn a repeatable workflow that you can apply to make product decisions. Use AI to support your job, while retaining full ownership and accountability.

Build repeatable AI-augmented workflows you can reuse in real product work

Learn how to use AI to accelerate customer discovery, validate solutions, and make better product decisions, without leaving your desk

Cohort 1

Product Innovation & AI Trainer

Capital One

Cisco

Wesco

Google

Valerio Zanini

Product Management and Innovation trainer. Author, "AI for Product Managers".

Cohort 2

Lead AI initiatives with clear goals, defensible evaluation, explicit risk decisions, and exec updates that drive alignment and investment.

CPO, GM xBraintrust, Nextdoor, OpenTable

Braintrust 🧠

Nextdoor

LiquidSpace I Work from where it works.

OpenTable

BlackRock

Elena Luneva

f-CPO. Product executive (Braintrust, Nextdoor, OpenTable, LiquidSpace)

Ex-Alexa AI Principal PM

Amazon

Elsevier

Schneider Electric

Polly Allen

Ex-Alexa AI PM turned founder at AI Career Boost

Magic

AI increases IC leverage, but it also breaks the management systems most teams rely on.Prototypes multiply. “Quality” becomes subjective. Risk can ship quietly. Leadership gets pulled into every review because no one is sure what good looks like, or who is accountable for evaluation, failure modes, and rollout decisions.If you’re a Director, Head of Product/Eng/Data, or VP with multiple AI initiatives in flight, you’re likely seeing the same pattern: lots of demos, uneven production outcomes, rising cost and reliability questions, and execs asking, “How do we know it’s good?” “What can go wrong?” “What’s the ROI?”This workshop gives you a practical operating system for leading AI-native work without slowing teams down.You’ll leave with:<ul><li>a portfolio and cadence that prevents orphan prototypes and experiments, </li><li>repeatable review process to assess risk and evaluation throughout projects, and</li><li>a new 'operating system' for AI-forward teams so that AI progress translates into ROI</li></ul>The result: faster alignment, fewer surprises, and AI work that ships to production with confidence.

Lead AI-heavy teams with new playbooks for prototypes, risk assessment, and eval

Install an AI-native operating cadence that keeps speed and alignment

Run AI risk reviews that drive decisions and confidence

Own and drive evaluation metrics and process, before and after launch

Reclaim 5 hours a week using new AI-first playbooks

Director/Head of Product: Leads AI initiatives; turns prototypes into production with clear quality, gates, and exec updates.

Eng leader (Sr Mgr/Dir/VP): Ships AI fast while managing reliability, security, and cost with consistent eval + risk reviews.

Data/ML leader (Dir/Head): Owns evals and performance; aligns product and execs with shared language and decision-ready tradeoffs.

Build, deploy, and scale real AI systems—transforming you from learner to job-ready AI Engineer.

Alpha

Beta

Charlie

Train Models. Build Systems. Deploy AI

Vivian Aranha

AI educator and engineer who builds and teaches production-ready AI systems.

Many people learn AI by watching tutorials or training models in isolation—but struggle when asked to build, evaluate, deploy, and maintain real AI systems. This course exists to close that gap.The critical challenge today isn’t learning algorithms—it’s turning AI knowledge into production-ready systems. Engineers often know Python or machine learning concepts but lack confidence in data pipelines, model evaluation, deep learning frameworks, and deployment workflows. As a result, projects stay in notebooks and portfolios don’t reflect real-world skills.This bootcamp is designed with empathy for that struggle. It takes you step by step from Python fundamentals to advanced deep learning and MLOps, always anchored in hands-on projects that mirror real engineering work. You won’t just train models—you’ll engineer complete AI solutions, tune them, deploy them, and understand how they behave in production.By the end, you don’t just “know AI.” You can build, explain, and ship AI systems with confidence—the exact skill employers and clients are looking for today.

Learn AI Engineering by Building Real Systems End-to-End

Build end-to-end AI systems

Master core machine learning techniques

Engineer features that improve model performance

Develop deep learning models confidently

Deploy and operationalize AI models

Think and work like a professional AI Engineer

Engineers and developers who want to transition into real-world AI engineering roles.

Data scientists seeking stronger system-building, deployment, and MLOps skills.

Students and professionals building an AI portfolio for jobs, freelancing, or startups.