Become the AI product manager teams fight to hire.
GreatFaculty is a 15-week live program that pairs classic product craft — discovery, strategy, analytics, growth — with the AI-native skills shaping 2026 hiring: evals, agentic systems, context engineering, and harness design. You leave with a shipped AI product, not just a certificate.
Illustrative — swap in your own alumni placements and hiring partners.
Placeholder metrics — replace with your own program numbers.
A program built to end in an offer, not a certificate.
Every cohort runs alongside structured, hands-on career support — not a bolt-on at the end.
Resume, rebuilt
1:1 review with a working PM. We reframe your experience around outcomes, not tasks, so transferable skills actually read as product skills.
A portfolio you can defend
Five graded projects plus a capstone, including the option to design, build, and ship your own AI product end to end.
Interview reps that count
Structured prep across product sense, metrics, strategy, and behavioral rounds — with mocks run by working PMs.
A warm network, not a job board
Referrals and openings sourced through alumni and hiring partners — not just a static listings page.
Not all AI PM programs are created equal.
A side-by-side of what's typically on offer elsewhere, versus what's actually inside GreatFaculty.
People who changed careers through this exact curriculum.
"I came in knowing how to sell software, not how to build it. By week six I was running real discovery interviews; by the buildathon I'd shipped something I was proud to show in interviews."
"What got me the US offer wasn't the curriculum on paper — it was the mock interviews. I'd been pressure-tested on metrics and product sense so many times that the real thing felt familiar."
"I already understood the tech. What I needed was a framework for product judgment, and that's exactly what the strategy and discovery weeks gave me."
Composite, illustrative testimonials — replace with quotes from your own alumni.
Everything you need to operate as an AI product manager.
The full build log — week by week, topic by topic, project by project. Nothing skipped, nothing generic.
Fundamentals of Modern Product Management
- The modern PM role across B2B and B2C
- The product life cycle: discovery, delivery, distribution
- Building genuine product sense
- Core hard and soft skills, and how to practice them
- Using AI as a PM without losing your judgment
- Tour of the AI tool stack: ChatGPT, NotebookLM, Gemini, Kraftful, ChatPRD
User & Market Research — Product Discovery
- Discovering, validating, and framing real user problems
- User psychology and motivation theory
- Surveys, interviews, and secondary research
- Personas and customer journey maps
- JTBD, 5 Whys, and the MOM Test
- Research pitfalls specific to AI products
- Competitive analysis with NotebookLM, Napkin AI
Product Strategy & Execution
- Building a vision from insight and opportunity
- The building blocks of product strategy
- Roadmaps that stay aligned to strategy
- Writing a PRD that actually gets built
- From PRD to shipped feature
- OKRs, sprints, and agile execution
- How AI is reshaping strategy work
- Drafting strategy and stakeholder artifacts with AI
Product Analytics
- Data-driven decision-making for PMs
- Choosing metrics by business type, incl. North Star
- Event tracking: users, events, properties
- Funnels, segmentation, cohort analysis
- Running experiments and A/B tests
- Data cleaning and de-duplication with AI
- Connecting your stack to GPT, Claude, or Llama
Generative AI — The Building Blocks
- Predictive AI vs generative AI
- How LLMs work: pre-training to fine-tuning
- The AI economy: infra, models, apps, providers
- Attention, tokenization, inference, RLHF — in plain language
- Finding the right AI use cases for your users
- The AI PM Stack: a 7-step build framework
System Architecture of AI Products
- Core components: data, models, context, tools, feedback loops
- Context engineering — Notion AI, Atlassian Intelligence, ChatPRD
- Advanced prompt engineering: few-shot, chaining, system prompts
- RAG for context engineering
- Fine-tuning vs RAG: a decision framework
Evaluations (Evals)
- Writing evals — the must-have AI PM skill
- What makes an eval effective
- Why evals matter more in AI than traditional software
- Working with stochastic, non-deterministic behavior
- Offline vs online evals, and how to integrate them
- Using evals to drive product improvement
AI Agents
- What agents are and how they work
- The AI Agent Stack: a 7-step build framework
- Practical agent applications inside a product
- Model Context Protocol (MCP) for tooling and distribution
- Build and deploy an agent of your own
Designing AI Product Experiences
- The Octopus Framework for AI product design
- Best practices for AI-native UX
- Designing around hallucination, latency, streaming, non-determinism
- Guardrails: regulation, trust, safety, security
- Choosing models and building feedback loops
AI Product Adoption, Growth & Scaling
- Data feedback loops and platform thinking
- Product-led growth in AI products, B2C and B2B
- What breaks when AI products scale
- How growth actually happened at AI-native products
10x-ing PM Output with AI
- A sane approach to using AI as a PM, not a crutch
- AI-assisted research and experimentation
- Using AI to build your portfolio
- AI for stakeholder management
- Building your own lightweight AI workflow tools
Harness Design & Engineering
- What harness engineering is, and why it matters for AI products
- Core elements of harness design
- Inside the architecture of Claude Code
- Inside the architecture of OpenClaw
Buildathon — Ship Your Own AI Product
- Finding a real opportunity and problem statement
- Writing the PRD for your idea
- Building an MVP with AI tools
- Setting up analytics and experimentation
- Getting real users
- Iterating on feedback, turning it into a portfolio piece
Breaking Into a PM Role
- Breaking in from non-PM backgrounds
- Resume and LinkedIn, rebuilt around transferable skills
- Product design, guesstimate, metrics, behavioral, strategy questions
- Take-home case study strategy
- Building a product portfolio
- Offer negotiation, mock interviews, expert resume review
Growth, Acquisition & Product Marketing
- Product-led growth fundamentals
- Growth loops and flywheels
- The AARRR (pirate) framework
- Acquisition: network effects, virality, referrals
- Activation, onboarding, and "aha" moments
- Retention, habit formation (Fogg Behavior Model)
- Pricing strategy and growth team structure
Tech for Product & Business Folks
- How the internet actually works
- Three-layer architecture: front-end, backend, databases
- Storage, databases, and SQL for PMs
- APIs and webhooks
- System design of products like Instagram and YouTube
- Git, GitHub, and deployment basics
- Cloud and AI/ML fundamentals · working well with engineers
Hands-on with the tools product teams run on.
Design & Wireframing
Execution & Delivery
Product Analytics
AI Productivity
Learn from people who've actually shipped.
Every mentor brings 8+ years of operating experience. Profiles below are illustrative — drop in your own instructor bios.
Growth & Product Leadership
Scaled a B2C ed-tech product from 250K to 3.5M monthly actives, and grew a fintech app from 10K to 500K users in a single year.
Roadmaps & Stakeholder Management
Built and scaled e-commerce and social-impact products from zero to several million users as a product director.
Fintech & Lending Products
Built a lending vertical from scratch at a top fintech, generating tens of millions of dollars in qualified leads in a single quarter.
Product Analytics
Set up the data and analytics function for product teams at a consumer lending company.
Course fees
Full AI Product Management Track
No-cost EMI available, from roughly ₹8,500/month. Many employers reimburse this program under L&D budgets — ask your manager.
Apply NowFor international candidates
Inclusive of taxes
Indicative pricing for Cohort 53 — confirm current fees and any active offers with an advisor before enrolling.
Join a counselling sessionEverything you need to know before joining.
What's the application process, and how big is each cohort?
You apply, complete a short screening call, and get an offer with your cohort start date. Cohorts are kept small enough that mentors know every participant by name.
How is the program delivered?
Live, instructor-led sessions over video, supplemented with recorded modules, hands-on assignments, and weekly office hours.
What if I can't attend a live session?
Every session is recorded and added to your portal within 24 hours, so you never lose access to the material.
Can I do this alongside a full-time job?
Yes — most participants work full-time. Sessions are scheduled on evenings and weekends, and the recorded library covers anything you miss.
How much time should I set aside each week?
Plan for roughly 8–10 hours a week: live sessions, assignments, and project work combined.
I'm a student or fresher — is this for me?
Yes. The program starts from first principles in Week 1 and is built to work for career-switchers and freshers as well as practicing PMs leveling up.
Will I get direct access to instructors and mentors?
Yes — unlimited 1:1 mentor calls are included, alongside live Q&A in every session.
What are the timings?
Live sessions typically run on weekday evenings and weekend mornings, in a timezone-friendly slot announced before the cohort starts.
Can I fast-track and finish sooner?
Yes — a fast-track option lets motivated participants compress the live schedule while still completing every project.
What's the full fee structure?
₹63,600 plus 18% GST (₹75,000 total) for the flagship program, with a no-cost EMI option. International candidates pay USD 1,000, inclusive of taxes.
What job assistance is included?
Resume optimization, portfolio building, structured interview prep, mock interviews, and referrals through our alumni and hiring-partner network.
Do I get a certificate?
Yes, on completing the program requirements, including the hands-on assignments and buildathon.
What support continues after the program ends?
Two years of portal access, weekly live office hours, and free transfers between cohorts if your schedule changes.
Can I talk to alumni before enrolling?
Yes — ask your advisor during your counselling session and we'll connect you with alumni from a relevant background.
Your next role is an AI product manager role.
Join the cohort, build a real AI product, and walk into interviews with proof — not just a transcript.