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.
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 when a product workflow needs a prompt, automation, agent, or multi-agent system. Define the responsibilities worth delegating and where product judgment must remain human.
Design and Build Your First AI PM Agent
Build the Customer Intelligence Agent end to end using a simple framework: Responsibility → Context → Instructions → Guardrails → Output. Test it against realistic product evidence.
Assemble Your Agentic AI PM Team
Add the Product Strategist and Product Challenger. Define what each agent owns, what context it receives, what it hands off, and how the three roles work together.
Validate the Workflow and Make the PM Decision
Pressure-test the agents, validate each handoff before passing it forward, run the full FlowPilot workflow, and use a Human PM Decision Gate to decide what happens next.
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 of ChatGPT, Claude, Gemini would be good to have.
Set Up Your Tools
Create your required accounts and confirm you can open the AI building tool 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 Before or After Workshop
1:1 session with Pri either before the workshop or after, so you can get your custom Agentic AI PM Team setup correctly.
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—notamál enfaldan 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$200
USD
11am–2pm EDT