Update -

Wednesday Batch is SOLD OUT & Enrolment is closed

Batch 2, starting Saturday (1st Nov) 9 AM PST (if you miss the first session, you can catch up with the ecording)

Price rising by $500 from 1st November

🚨ANNOUNCEMENT:

The October-November Cohort would be our last Cohort of 2025.

Discounts would be on a reducing seats/dates basis

1) $400 Off with Code OCT, till 26th Oct Only

2) $350 Off with Code NOV, till 29th Oct Only

NO DISCOUNTS AFTER 29th OCTOBER EOD.

Questions?

Meet our team here - https://calendly.com/team_maheshyadav/

What’s Included (Total Value: $4500+):

✅ Full GenAI Cohort Experience (Learning + Building + Career Accelerator Guidance)

✅ Dedicated Tech Expert for Hands on Labs/Building your AI Prototype

✅ 20+ live sessions with Mahesh during the cohort and countless more on advanced trending topics even after the cohort's lifetime.(Maximum across Maven)

✅ 1:1 Mentorship with Mahesh Yadav (Worth $1000)

What You’ll Achieve with this Agentic AI PM Program with MAANG leader (Learning+Building Products+Interview Prep: All At One Place)

- Build Real AI Product Intuition – Learn to translate AI capabilities into user-centric features.

- Hands-on AI Labs & Tools – Using various AI tools like V0.dev, crew.ai, n8n, Langchain, OpenAI agents, Microsoft Co-pilot studio, Vertex.ai, AWS Flow, Azure Evaluator, Google Colab, and OpenAI Enterprise with or without needing to code.

- Craft a GenAI Portfolio – Complete real case studies and projects to showcase your AI skills by building MAANG-level AI PRD.

- Crack AI PM Interviews with Confidence – Proven frameworks, mock interviews, and personalized feedback.

- Join a Network of 5000+ AI PMs – Weekly syncs, expert sessions, and lifetime support. Join Mahesh on a weekly FREE session in the community to stay updated on the latest.

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COURSE CONTENT

Week 1: Problem Framing and AI Solutioning

Objectives

- Translate business needs into solvable AI problems with clear success metrics.

- Choose between rule‑based and ML‑based approaches; draft an initial PRD.

Lectures & Topics

- AI/ML Product Management landscape; AI PM roles, stakeholders, expectations.

- Problem framing, hypothesis testing, and metric selection.

- Rule‑based vs. ML‑based systems.

- History and current landscape of Agentic AI.

Labs

- Workshop 1: Rule‑based vs. ML‑based decisions and feature selection for agents.

- Workshop 2: PRD kick‑off and structure.

Project

- Deliverables: PRD Sections 1–3 (Problem, Solution, Core Metric) using the provided checklist.

- Outcome: Validated problem statement, candidate solution, and measurable success metric ready for iteration.

Week 2: Foundations, Prompting, and No‑Code Agent Build

Objectives

- Understand core ML concepts; apply prompt engineering to prototype agents.

- Stand up a simple frontend + AI backend to validate feasibility.

Lectures & Topics

- Neural networks basics; DL vs. traditional ML.

- Supervised/unsupervised/reinforcement learning.

- Prompt engineering techniques (zero/few‑shot, role, and tool prompts).

Labs

- Lab 1: No‑code AI agent via prompt engineering.

- Lab 2: Custom frontend + backend using OpenAI/Gemini/Claude with V0.dev and n8n.

Project

- Deliverables: Working prototype demonstrating prompt patterns and model integration.

- Outcome: Functional agent prototype that proves feasibility and early user value.

Week 3: Prioritization, Roadmapping, and Agentic RAG

Objectives

- Prioritize features by value, cost, and risk; produce an MVP→Phase 2 roadmap.

- Add external knowledge via RAG and plan memory strategies for relevance.

Lectures & Topics

- Product roadmap and prioritization (MOAT and cost).

- AI stack and team roles (data, training, inference, compliance); LLM vs. SLM.

- Agentic RAG concepts; transformers overview.

Labs

- Lab 1: Langflow RAG and Agentic RAG (incl. graph RAG), signal extraction, memory, context checks.

- Lab 2: Connect to Supabase, add auth, capture feedback with an Agentic RAG backend.

Project

- Deliverables: PRD Sections 4–5 (Prioritization; Roadmap: MVP, Phase 1, Phase 2).

- Outcome: Risk‑aware roadmap and knowledge‑augmented agent plan with clear milestones.

Week 4: KPIs, Evaluations, and Responsible AI

Objectives

- Define agent KPIs and design evaluation plans at model and agent levels.

- Operationalize Responsible AI practices and compliance checks.

Lectures & Topics

- KPIs for agents; evaluating models and agents; precision vs. recall.

- Responsible AI framework: risks, mitigations, ethics.

- Ecosystem overview: EU AI Act, US AI Bill of Rights, leaderboards, model cards.

Labs

- Workshop: Precision vs. recall; apply to task metrics and thresholds.

- Community Session: Building safe and responsible AI (expert insights).

Project

- Deliverables: PRD Sections 6–7 (Evaluations; Responsible AI, incl. AI Act checks).

- Outcome: Measurable, compliant evaluation plan with defined safety and oversight gates.

Week 5: Evaluations in Practice and Multi‑Agent Systems

Objectives

- Implement practical evaluation pipelines and guardrails end‑to‑end.

- Explore multi‑agent architectures with reflection and human‑in‑the‑loop.

Lectures & Topics

- Why single agents underperform; moving to multi‑agent ROI.

- AI/ML frameworks for agentic systems; selection trade‑offs.

Labs

- Lab 1: LLM‑as‑a‑Judge evaluation setup and scoring.

- Lab 2 : Azure predefined evaluators (relevance, fluency, coherence, safety).

- Lab 3: Multi‑agent lab with guardrails, reflection, and HITL using CrewAI.

Project

- Deliverables: Evaluation harness + guardrail configs; updated PRD referencing test coverage.

- Outcome: Tested agent with baseline metrics and safety thresholds for “safe‑to‑ship.”

Week 6: GTM, Pricing, and Advanced Tools

Objectives

- Build pricing and GTM plans grounded in AI cost structure and growth strategy.

- Strengthen defensibility via fine‑tuning and modern tool‑calling protocols.

Lectures & Topics

- ML‑based product pricing; pricing for growth and adoption.

- Fine‑tuning for MOAT; MCP and A2A/ACA protocols; tool selection.

Labs

- Lab 1: Enterprise automation with Microsoft Power Automate; contrasts with copilots.

- Lab 2: Fine‑tuning LLMs with LoRA.

- Lab 3: Tool calling with MCP (e.g., Claude with puppeteer for computer control).

Project

- Deliverables: PRD Section 8 (Pricing); 1‑page GTM; rollout checklist.

- Outcome: Actionable GTM and pricing plan with technical readiness for scale.

Week 7: Marathon and Pitch Day

Objectives

- Finalize artifacts, harden demos, and craft a compelling narrative.

- Deliver a credible pitch aligned to KPIs and Responsible AI commitments.

Lectures & Topics

- Pitch preparation: story, metrics, objection handling.

Labs

- Rehearsal runs; polish eval dashboards and guardrail evidence.

Project

- Deliverables: Final demo, PRD v1.0, evaluation matrix, KPI snapshot, pitch deck.

- Outcome: Production‑credible agent, documented evaluations, clear GTM path, confident pitch on Pitch Day.

What you’ll take away from the cohort

✅ Spotting high-impact AI use cases in any business

✅ Master agentic design (memory, knowledge, reflection, focus)

✅ Build multi-agent workflows with tools & data

✅ Design and write MAANG-level PRDs

✅ Use advanced prompting (CoT, ToT) for real applications

✅ Deploy agents using Langflow, CrewAI, OpenAI, Vertex AI, and more

✅ Grasp core ML concepts — neural networks, transformers, memory mgmt

✅ Learn pricing, GTM, and scaling strategies for AI products

✅ Work on real MAANG-level case studies

Whether you come from a tech or non-tech background, you won't just build with AI — you'll walk in already appearing like an insider.

This is your final chance to join the most practical, hands-on AI PM program at the current price.

Special Pricing for Team Enrollment/Corporate training (5 or more) 

📞 Have questions?

Meet our team here https://calendly.com/team_maheshyadav/

And we’ll walk you through everything.

Our Community

We're the only AI PM certification course that genuinely helps and tracks your success even after cohort completion.

We are really proud of 27% of our cohort members who have successfully transitioned into AI PM roles. We achieve these results through:

- 50+ written lessons

- 10+ live workshops (beyond recorded content)

- 20+ live AMA sessions directly with Mahesh

- Continued support during interviews and continuous learning via weekly sessions after the cohort

- Non-technical PMs are fully supported and encouraged to dive in—we provide extensive support hours to help.

Our mission is to make this the only AI course you'll need in 2025 (period). To ensure this, we've added hands-on learning labs and strong technical support that empowers everyone—no coding or technical background required. Here, we will empower you to confidently identify, create, evaluate, and launch production-ready agents using GCP Vertex AI, Langflow, Crew AI, Azure Evaluators SDK, and Azure Co-pilot Studio.

Get to know Mahesh

Mahesh Yadav is your mentor and guide to success in AI product management. With over 20 years of experience and 10+ years building AI-powered products at Google, Amazon, Meta, and Microsoft. Mahesh has 9 patents as a primary innovator in AI training and Power management. He has presented at premier conferences such as Nvidia GTC, Microsoft Build, and AWS re: Invent. Mahesh brings firsthand insights from advising fast-growing AI startups and collaborating with senior leaders at Google, Meta, and Amazon, giving you an inside look at what truly drives AI innovation in top tech giants and AI startups in the Bay Area.

Deep Expertise: Mahesh led the expansion of PyTorch into PyTorch Distribution and contributed to Meta’s first GPT3-scale training model (OPT) in 2019. His work spans key AI technologies, including recommendation systems, PyTorch, Agents for AWS Bedrock, and multi-agent for GCP.

Practical Insights: His teaching uses real project examples to deliver actionable strategies you can implement immediately. He has been teaching for the past 15 years at Microsoft. He taught as a TEALS instructor for 3 years, then he taught AI courses internally for fun at Meta and MSFT. For the last 3 years, he has taught 10k+ across Free and Paid channels. 

Impact he left: Over 3000 professionals have upskilled through his courses, many now holding roles at top AI companies

Special Pricing for Team Enrollment/Corporate training (5 or more) 

📞 Have questions?

Meet our team here https://calendly.com/team_maheshyadav/

And we’ll walk you through everything.