3 Agents: Build your AI PM Team, For Product Managers
Priyanka Shetty
AI Product Leader & Builder
Build Your AI Agentic PM Team
AI can summarize research, draft PRDs, analyze customer feedback, and generate ideas.
But the bigger opportunity is learning how to design specialized AI agents that work together across a real product decision.
In this 3-hour hands-on workshop, you’ll design, build, and test a three-agent AI PM team using a realistic B2B SaaS case.
You’ll build:
Customer Intelligence → Product Strategist → Product Challenger → Human PM
Along the way, you’ll learn how to define clear agent responsibilities, give each agent the right context, create reliable handoffs, pressure-test outputs, and decide where human product judgment must remain.
We’ll use Claude Code to bring the system to life, but the architecture you learn is tool-agnostic and can be adapted to other AI platforms.
You won’t leave with three disconnected prompts.
You’ll leave with a reusable model for designing coordinated AI product workflows you can adapt to your own work. You will also leave knowing how to build the next agent yourself, from a blueprint, without a scaffold.
What you’ll learn
Design, build, and validate a three-agent AI PM team you can adapt to your own product workflows.
Distinguish prompts, workflows, agents, and multi-agent systems.
Identify where judgment is required versus simple execution.
Decide where AI should act and where product judgment must stay human.
Define responsibility, context, instructions, guardrails, and output.
Give each agent only the context needed for its role.
Create outputs another agent can reliably use.
Build Customer Intelligence, Product Strategist, and Product Challenger.
Use realistic product evidence rather than polished demo data.
Keep each agent’s responsibility intentionally distinct.
Define what each agent passes to the next role.
Diagnose whether a failure comes from the instructions, context, workflow, or model.
Prevent context debt and role drift across the workflow.
Use break tests to expose unsupported claims and weak assumptions.
Separate supported facts, hypotheses, and unknowns.
Validate outputs before the next agent relies on them.
Use AI to understand, recommend, and challenge.
Make the final decision through a Human PM Decision Gate.
Apply the same architecture to your own product workflow.
Workshop agenda
Diagnose the PM Workflow
Decide whether a workflow needs a prompt, an automation, an agent, or a team using a five-question test. Choose a real workflow from your own week to design around.
Design and Build Your First AI PM Agent
Write the agent yourself using Responsibility, Context, Instructions, Guardrails, and Output. Every claim it makes must cite the evidence and separate supported facts from hypotheses and unknowns.
Build the Strategist From Your Own Blueprint
Complete the Agent Blueprint, then have Claude Code generate the agent from it. Compare your version with a reference build, and leave with a method you can reuse for any agent you design next.
Challenge and Break Your Team
Add the Product Challenger and see why it needs different context and a different role than the Strategist. Run break tests, including a case where the right answer is "I don't know," and diagnose eac
Decide as the Human PM
Run the full FlowPilot workflow and validate each handoff. At the Human PM Decision Gate, write a memo: your recommendation, evidence, unknowns, and whether you accept, modify, or reject.
Design Your Own Agent
Blueprint a real agent for your own work, get peer review in small groups, and leave with a plan for Monday.
Learn directly from Priyanka
Priyanka Shetty
AI Product Leader (Oracle, S&P Global, Weill Cornell) | AI Strategist & Founder
Who this workshop is for
Individual Contributor PMs building AI features
Own AI initiatives but can't yet evaluate architecture, want hands-on build skills.PMs targeting AI-native roles
Job specs now expect agentic fluency. Want proof you've built one, not just read about it.Product leaders scoping AI initiatives
Need to evaluate engineering proposals with real technical judgment, not defer entirely or guess.
Prerequisites
No coding or AI engineering experience is required.
You should be comfortable with core product-management concepts. Basic experience using ChatGPT or Claude would be good to have.
Set Up Your Tools
Create your Claude Code account and confirm you can open it before the live workshop.
Test the Starter Project
Open the provided project and complete the setup check to confirm everything works correctly.
What's included
Live sessions
Learn directly from Priyanka Shetty in a real-time, interactive format.
Lifetime access
Go back to course content and recordings whenever you need to.
1:1 with your instructor
Book your 1:1 when you enroll
Community of peers
Stay accountable and share insights with like-minded professionals.
Certificate of completion
Share your new skills with your employer or on LinkedIn.
Live Hands-On Workshop
Build one AI PM agent end to end, then connect it with two specialist agents using guided scaffolds.
Agentic AI PM Team Scaffold
Start with a reusable three-agent system designed around real product management workflows.
AI Agent Blueprint
Define each agent’s role, goal, inputs, reasoning, outputs, guardrails, evaluations, and handoffs.
Realistic PM Evidence Pack
Build and test using customer research, product data, and business context, not a simple demo.
Agent Templates and Prompts
Customize ready-to-use instructions for specialist agents instead of starting every build from scratch.
Testing and Evaluation Toolkit
Evaluate output, evidence, identify failure modes, and improve your agent team systematically.
Maven Guarantee
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Frequently asked questions
Maven for Teams
Reimbursement
Get your company to pay
Everything L&D needs: email template, receipts, and certificate of completion.
Get reimbursedTeam discount
Learn with your teammates
Save 20%+ when 2 or more teammates enroll in the same cohort.
Save 20%+ with a teamPrivate cohort
Run a cohort for your org
A dedicated cohort with a custom schedule and curriculum, tailored to your team.
Book a private cohort$350
USD
12–3pm EST