AI-Native Product Strategy: Build for Intelligence, Not Features
Join Sanaz Alexander (Director of Product Management · Meta) for a free live session.
Sanaz Alexander
Director of Product Management · Meta
⭐ 4.9 / 5
Most product leaders are adding AI to their roadmap. The best ones are rebuilding their strategy around it.
Bolting AI onto existing products is not a strategy. This 8-week sprint is for Directors, VPs, and Heads of Product who need to move from incremental thinking to AI-native leadership — covering strategy, defensibility, portfolio management, monetization, operating models, discovery, and transformation. Every week ends with a deliverable your org can act on.
What You'll Learn
AI-Native Product Strategy
Shift from incremental AI thinking to designing products where intelligence is the foundation — not a feature layer. Build the mental model for probabilistic, AI-native product design.
Defensible Moats in the AI Era
Learn why model-level differentiation is short-lived and how to build durable advantage through proprietary data loops, workflow integration, and continuous learning systems.
AI Portfolio and Monetization
Move from disconnected AI experiments to an intentional portfolio strategy. Design AI-native pricing models that reflect variable usage, inference costs, and outcome-based value.
Pilot to Scale
Close the gap between impressive demo and reliable production. Design AI systems for trust, failure modes, and quality — with evaluation frameworks and cost-performance tradeoffs built in.
Who Is This For?
This sprint is designed for:
Group PMs, Directors, and Heads of Product
Responsible for product vision and roadmap across AI-first or AI-transforming organizations — who need the full leadership toolkit, not just feature-level AI knowledge.
Founders Building AI Products
Who need to make durable decisions on strategy, defensibility, monetization, and operating model before those decisions get expensive to change.
VPs and Product Leaders at Scale
Owning AI strategy at the organizational level — responsible for multiple teams, product lines, or the full P&L of an AI-powered business.
Sprint Outline
8 weeks · 3 sessions per week
Projects You'll Ship
Leave with real work to show, not just a certificate.
AI-Native Strategy + Moat Map
A strategy memo identifying an AI-native opportunity — with a moat map that diagnoses the current sources of defensibility, where they erode in an AI-commoditized world, and the prioritized investments that rebuild durable advantage. The artifact that answers 'why will we still win in two years?'
AI Portfolio + Monetization Model
A structured AI portfolio across three time horizons with clear prioritization criteria and a scale/kill decision framework — plus an AI-native monetization model with cost-value tradeoffs mapped out. The two documents that turn AI chaos into a strategy your CFO and board can fund.
AI Product Leadership Strategy Capstone
Your complete AI product leadership strategy: operating model, AI-powered discovery workflow, production readiness framework, transformation roadmap, and synthesis across all eight weeks — presented live to the cohort. The portfolio piece that demonstrates senior AI product leadership at the organizational level.
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 moat mapping framework in Week 2 changed how I present strategy to my board. I stopped talking about features and started talking about data loops and switching costs. Completely different conversation."
Priya Shah
VP of Product · Notion
⭐⭐⭐⭐⭐
"Week 4 on monetization was worth the entire sprint. We were about to reprice our AI product the wrong way — usage-based when we needed outcome-based. Sanaz's framework caught it before we shipped."
Marcus Chen
Head of Product · Stripe
⭐⭐⭐⭐⭐
"I came in with 15 disconnected AI initiatives and no way to prioritize them. I left with a portfolio framework, a kill list, and a 3-horizon roadmap my CEO funded in the next planning cycle."
Jordan Kim
Director of Product · Rippling
Sprint Schedule
All sessions are instructor-led and live. Recordings available within 24 hours.
SUNDAY
9:00 AM PDT
Live ClassStrategic deep dive with Sanaz — frameworks from Meta and Disney, real product case studies, and live working sessions. Every Sunday ends with a usable artifact.
WEDNESDAY
6:00 PM PDT
Lab SessionApply the week's framework to your own product or org. Bring real constraints, real decisions, real blockers.
THURSDAY
6:00 PM PDT
Build & ShipFinish and pressure-test your weekly deliverable with peer review and instructor feedback before you submit.
Frequently Asked Questions
AI-Native Product Strategy: Build for Intelligence, Not Features
with Sanaz Alexander · Director of Product Management, Meta
What you'll walk away with:
🎁 Bonus for attendees:
Get "The AI Product Leader Starter Kit"
AI-native opportunity framework, moat mapping template, and AI portfolio prioritization worksheet — ready to apply to your roadmap this week
Claim your free seat
Skills you can deploy on Monday morning.