Nicolas LIATTI

Use AI to Ship Outcomes, Not Features

Nicolas Liatti

Product Leader | ex-Adobe

How to translate stakeholder asks into testable outcome hypotheses before you write a single spec.

Diagnose any feature request in 60 seconds

The leverage points where AI actually changes PM decisions, not just your workflow.

Use AI to compress your feedback loop

A one-page template that replaces the feature spec and gets stakeholders aligned on success metrics upfront.

The Outcome Brief: your new first artifact

Stop executing others' roadmaps. Build strategy executives fund, speak the language of business, and win stakeholder buy-in.

VP Product. 300+ PMs Stuck to Strategic

Deloitte

PRGX Global

FinThrive

Healthmine

Brennan Collins

Startup & Enterprise Product Exec. Coached 300+ PMs from Stuck to Strategic

Jan-Feb 2026

March 2026

AI can write your PRD in 30 seconds. But it can't figure out which problem to solve, get buy-in from your VP, or connect your feature to revenue targets executives fund.You're competent. You know the fundamentals. But you're stuck in delivery mode, executing roadmaps you didn't create, managing requests you can't push back on, watching less capable PMs get promoted because they learned to speak the language of business.The gap isn't talent. It's significance.You produce work that disappears. You need work that registers as strategically important to people with power. AI won't fix this. It'll just help you execute faster on things nobody notices.This course teaches you both: master the craft that makes you significant, then sharpen the tool that multiplies your impact.In 4 weeks, learn frameworks AI amplifies but can't replace:<ul><li>See how it's done: Live examples showing good → better → best execution</li><li>Practice on your work: Multiple exercises per session, immediate application</li><li>Build then sharpen: Create artifacts Monday-ready, get prompts that 10x them</li><li>Know when AI's enough: High-stakes strategy needs your judgment. Repetitive work doesn't.</li></ul>Stop being invisible. Start being significant.

Master Your Craft First.  Then Let AI Multiply Your Significance as a PM Leader

Think like a business owner, not a delivery manager

Map customer needs to business metrics executives care about

Craft a vision that inspires and a strategy that creates confidence

Transform stakeholder feature demands into defensible strategic moves

Build a Business; Not just a Product

Position yourself for promotion and lead with executive presence

This is not an entry-level course.  These are advanced topics.  See my free content for PM foundations and breaking into product management.

3 to 10 years experience in Product Management

No one-and-done projects here.  You need to have felt the joy and pain of good and bad decisions (yours or someone else's).

Experience shipping multiple iterations of the same product

Not just your salary (but that comes with it)... You don’t need to be a Director of PM yet, but you should want to become one.

An intrinsic desire to grow your responsibility & challenges

Mid-career PMs stuck in delivery mode who want to think more strategically and earn a seat at the decision-making table.

Experienced product managers who want to speak the language of business and defend their roadmap with metrics executives respect.

PMs ready for promotion or exploring product leadership who want to operate like strategic leaders, not order-takers.

Acquire and develop a critical skill for product managers who are leading and contributing to AI products.

February 2026 (please delete)

Feb 2026

GenAI Product Builder @ Google, ex-Meta

Marily Nika, Ph.D AI/ML

Product Manager AI&ML @ Google

Diego Granados

Senior Data, ML and GenAI Scientist

SHI International

National Association of REALTORS

George Zoto

Senior NLP/AI Scientist

December 2025

Cohort 4

“Does it work?”... “Is it good enough?”... “Can we ship it?”...How do you answer these questions for AI products? You’re responsible for “running evals” but what does that mean?How do you choose the right metrics, interpret fuzzy results, and make a confident decision?This course gives you a framework to do just that.<ul><li>Map user value to evaluation (eval) objectives so your metrics aren’t abstract. Define success then translate it into measurable criteria.</li><li>Choose metrics you can actually maintain: capability, safety, UX friction, latency, cost and “does this reduce support tickets or increase activation.”</li><li>Set ship/no-ship thresholds you can defend to leadership.</li><li>Build lightweight workflows that work in real teams: human review where it matters, automation where it lasts, documentation that drives decisions.</li><li>Consider domain constraints (e.g., healthcare safety) and know what to avoid: silent failures, misleading proxy metrics and tests that don’t reflect production.</li><li>Tie everything to ROI: impact vs unit cost, eval coverage vs reliability, and the minimum viable monitoring you need post-launch.</li></ul>Experience AI evals through a case-based approach with a real AI product that we evaluate together.

Eliminate uncertainty in shipping AI features

Make confident ship or hold decisions for AI features

Translate user value into clear evaluation goals

Choose the right metrics for capability, safety, UX, and cost

Set defensible thresholds leadership will trust

Build lightweight evaluation workflows teams can maintain

Navigate domain constraints and avoid common failures

PMs leading AI features, growth, or platform initiatives

PMs who partner with ML teams and want to set evaluation standards

PMs who need to make clear “ship or hold” calls without doing the engineering

Lead AI initiatives with clear goals, defensible evaluation, explicit risk decisions, and exec updates that drive alignment and investment.

CPO, GM xBraintrust, Nextdoor, OpenTable

Braintrust 🧠

Nextdoor

LiquidSpace I Work from where it works.

OpenTable

BlackRock

Elena Luneva

f-CPO. Product executive (Braintrust, Nextdoor, OpenTable, LiquidSpace)

Ex-Alexa AI Principal PM

Amazon

Elsevier

Schneider Electric

Polly Allen

Ex-Alexa AI PM turned founder at AI Career Boost

Magic

AI increases IC leverage, but it also breaks the management systems most teams rely on.Prototypes multiply. “Quality” becomes subjective. Risk can ship quietly. Leadership gets pulled into every review because no one is sure what good looks like, or who is accountable for evaluation, failure modes, and rollout decisions.If you’re a Director, Head of Product/Eng/Data, or VP with multiple AI initiatives in flight, you’re likely seeing the same pattern: lots of demos, uneven production outcomes, rising cost and reliability questions, and execs asking, “How do we know it’s good?” “What can go wrong?” “What’s the ROI?”This workshop gives you a practical operating system for leading AI-native work without slowing teams down.You’ll leave with:<ul><li>a portfolio and cadence that prevents orphan prototypes and experiments, </li><li>repeatable review process to assess risk and evaluation throughout projects, and</li><li>a new 'operating system' for AI-forward teams so that AI progress translates into ROI</li></ul>The result: faster alignment, fewer surprises, and AI work that ships to production with confidence.

Lead AI-heavy teams with new playbooks for prototypes, risk assessment, and eval

Install an AI-native operating cadence that keeps speed and alignment

Run AI risk reviews that drive decisions and confidence

Own and drive evaluation metrics and process, before and after launch

Reclaim 5 hours a week using new AI-first playbooks

Director/Head of Product: Leads AI initiatives; turns prototypes into production with clear quality, gates, and exec updates.

Eng leader (Sr Mgr/Dir/VP): Ships AI fast while managing reliability, security, and cost with consistent eval + risk reviews.

Data/ML leader (Dir/Head): Owns evals and performance; aligns product and execs with shared language and decision-ready tradeoffs.

Using AI in product management is not just about getting better at ChatGPT. It's about how to leverage AI across the product development life cycle (PDLC) to accelerate, expand, and simplify what's possible. Unfortunately, most AI courses for PMs focus on how to build AI-powered features. But PMs can benefit from AI practices regardless of the type of product they are building. This is the focus of this course: helping PMs expand the daily practice of product management and giving PMs super powers. Over two weeks, you’ll learn—by doing—how to use AI to accelerate discovery, synthesize insights, explore solutions, and support decisions, while understanding where AI helps and where it can mislead. This is a hands-on, instructor-led cohort for PMs who make real product decisions. Course Structure (PDLC-Aligned):1.	Discover – AI-Accelerated Customer Discovery2.	Define – Insight Generation &amp; Problem Framing3.	Design – Ideation &amp; Solution Shaping with AI4.	Drive – Validation of Solutions, Decision-Making, Risk &amp; Trust Each session builds on the previous one with hands-on exercises on a real product idea. You practice using AI tools and refining your prompts while developing a critical mindset for when and how AI makes sense. How the Course Works: Duration: 2 weeks (short, intensive, focused) + Graduation Demo dayFormat: Instructor-led cohort with 4 live sessions (you get help as you go)Sessions: 2 sessions per week (gives you time to internalize)Between sessions: Hands-on individual assignments (to build the practical muscles) You will:•	Work on a shared real-life product case in small groups•	Complete individual exercises for each phase of the PDLC•	Review and discuss peers’ work•	Learn through comparison, challenge, and reflection•	Group collaboration is encouraged, but individual practice is required. Instructor:•	Author of "AI for Product Managers"•	Product leader with hands-on experience applying AI to real product work•	Focused on practical frameworks, not theoretical AI•	10-year experience running cohort-based training sessions for Product Managers This course is grounded in real-world product decision-making.

Get AI super powers to grow in your PM job

Course syllabus

Interactive sessions with the instructor to learn new topics, review assignments, and get support.

Tuesdays & Fridays

After each session, you work on a real product using the AI tools and practices learned in the session. This builds the muscles and your repeatable workflow.

Hands-on Assignments

At the end of the course, we'll meet for a final demo of the products built by each team and to get additional support.

Graduation Demo Day

Course schedule

Product Managers, Senior PMs, Group PMs. Product Leaders responsible for discovery and decision-making.

PMs who want to move beyond “AI curiosity” to real, practical capability. PMs who want hands-on practice to accelerate their own product job

This course is not a beginner introduction to product management or a tutorial on ChatGPT. It's a deep-dive on how to use AI in product work

Who is this course for

What you’ll get out of this course

Understand how AI expands each of the PDLC phases in Discovery, Define, Design, and Drive. Accelerate your process from problem definition to idea validation and drive innovation.

Accelerate your Product Management job

Learn how to use AI for customer and market Discovery, from creating synthetic users and interview guides, to conducting customer interviews. All with a critical eye focused on strategy.

Use AI to accelerate customer discovery without losing skepticism or empathy

Learn how AI can accelerate and expand insight generation, interview synthesis, and problem definition. Define problems without inventing false certainty.

Apply AI to synthesize insights and frame problems without inventing certainty

In the Design and Drive phases, AI can accelerate and expand ideation and problem-solution fit. Learn how to use AI to ideate, prototype, and validate new ideas quickly.

Use AI to expand solution space and prototype quickly, without premature convergence

Practice real-life product decisions while working hands-on with AI tools. Learn a repeatable workflow that you can apply to make product decisions. Use AI to support your job, while retaining full ownership and accountability.

Build repeatable AI-augmented workflows you can reuse in real product work

Learn how to use AI to accelerate customer discovery, validate solutions, and make better product decisions, without leaving your desk