Agent-Native Product Design: Where Agents Do the Work
Join Sanaz Alexander (Director of Product Management · Meta) for a free live session.
Sanaz Alexander
Director of Product Management · Meta
⭐ 4.9 / 5
Your product still assumes a human does the work. Agents change that entirely.
Most product leaders understand that AI is changing everything. Few know how to design for it — when agents replace users as the primary operator, when to give systems autonomy versus control, and how to measure behavior instead of just outputs. This 8-week course builds the full product leader toolkit for the agentic era: system design, strategy, evaluation, economics, and the workflows to run your own team at 10x leverage.
What You'll Learn
Agent-Native Product Design
Identify which parts of your product should be agent-driven and redesign workflows where agents replace manual steps — with a clear framework for autonomy, control, and user intent.
Agent Workflow Architecture
Break complex workflows into agent-executable steps, define tools and actions, and manage task dependencies — moving from prompt to structured multi-step system.
Evaluation and Trust Framework
Define success for agent behavior — not just outputs. Build evaluation frameworks that measure reliability, monitor performance in production, and design user trust when systems act on their behalf.
Agent Economics and Strategy
Make strategic decisions about when agents create real value and when they add unnecessary complexity. Understand cost structures, balance performance against spend, and integrate agents into your roadmap.
Who Is This For?
This course is designed for:
Product Managers Building AI Features
Who are adding AI to existing products and need a strategic framework for when and how agents should replace or augment user-driven workflows.
Senior PMs and CPOs
Who own AI product strategy for their org and need to make confident decisions on agent investment, autonomy design, and the economics of running agents at scale.
PMs Transitioning to Agentic Roles
Who are moving into roles where agentic systems are the primary product surface — and need the full toolkit: design, evaluation, human-in-the-loop patterns, and cost management.
Course Outline
8 weeks · 3 sessions per week
Projects You'll Ship
Leave with real work to show, not just a certificate.
Agent-Native Product Design + Workflow Document
A redesigned product workflow where agents replace or augment manual steps — with an autonomy boundary map, tool definitions, failure modes, and recovery paths. The artifact that replaces a vague 'AI feature' brief with a system engineering can actually build.
Agent Evaluation Framework + HITL Design Spec
A complete evaluation framework covering success definitions, measurement plan, and trust design patterns — plus a human-in-the-loop specification with escalation paths, approval systems, and intervention design for a real agent workflow.
Agent Product Strategy Capstone
Your full agent product strategy: prioritised use case map, investment thesis, progressive autonomy roadmap with risk gates, cost model, and personal PM agent stack. Presented live to the cohort — the portfolio piece that demonstrates complete product leadership in the agentic era.
Your Instructors
Sanaz Alexander
Director of Product Management · Meta
⭐ 4.9 / 5
Sanaz is a Director of Product Management at Meta, where she has led AI/ML-powered workflows that transformed enterprise customer experiences — from automated credit decisioning to billing and hardware purchase flows, reducing manual workload by 60%. Previously at Disney, she owned product strategy across Disney+ and ESPN+, scaling streaming experiences for tens of millions of users across international markets. She brings 12+ years of 0→1 product experience across AI, PLG, and agentic systems at scale.
What Students Say
⭐⭐⭐⭐⭐
"The autonomy design framework from Week 5 is now how we scope every AI feature. We stopped shipping agents with too much trust and not enough oversight — and our incident rate dropped."
Jordan Kim
Senior PM · Stripe
⭐⭐⭐⭐⭐
"Week 6 alone was worth the sprint. I set up three agent workflows for my own PM work and recovered 6 hours a week. The personal stack is something I use every single day."
Priya Mehta
Director of Product · Notion
⭐⭐⭐⭐⭐
"Sanaz brings real experience — not theory. Every framework she taught came with a Meta or Disney example that made it immediately concrete. This is the most applied AI product course I've taken."
Marcus Chen
CPO · Rippling
Course Schedule
All sessions are instructor-led and live. Recordings available within 24 hours.
SUNDAY
9:00 AM PDT
Live ClassDeep dive with Sanaz — frameworks, case studies from Meta and Disney, and live design exercises. Every session ends with a working artifact.
WEDNESDAY
6:00 PM PDT
Lab SessionStructured lab on your own product. Bring real use cases, real workflows, real blockers.
THURSDAY
6:00 PM PDT
Build & ShipFinish and test your weekly deliverable with peer review and instructor feedback before you submit.
Frequently Asked Questions
Related reading
The JD-backed research behind this course — from Dexity Intel.
How to Become an AI Product Manager in 2026 →How far do you want to go?
Start free to experience our offering, choose the program length you would want to commit to.
You build. Nobody demos at you.
Every session is follow-along — you build the thing yourself while a practitioner works beside you. That is why the hours look long: they are yours to build in, with an expert on hand to guide you. None of it is a traditional lecture.
In the session, you'll: