Alina Bezchotnikova

AI-Powered Discovery for Solo and Small Teams

Principle UX designer @ Aize

Learn to use AI to transform a product idea into a prioritized list of testable assumptions

Map Your Riskiest Assumptions in Under an Hour

Discover how to conduct lean validation conversations

Extract Insights from 5 Conversations

Get the complete toolkit and process for running discovery when you have no team and no budget.

Build Your Solo Discovery Workflow

Talk to customers. Test assumptions. Build with conviction.

Head of Product | x-Oracle, Autodesk

Oracle

Autodesk

Stanford University

National Peace Corps Association

Arup

Moiz Kapadia

Fractional Head of Product | ex-Oracle, Autodesk, Stanford alum

Cohort 3

Cohort 4

In 4 weeks, decide what to build.You know that Customer Discovery is a core skill for Product Managers. It's in every job description and you're expected build a customer centric product.When you showed up, your product leadership is too busy for structured discovery. Or worse, your team doesn't talk to customers.But you're still expected to deliver a roadmap that moves the needle.Without discovery, you build off loudest voices—sales demands, customer complaints—but those don't make great products.AI-powered discovery sprints change that.The best PMs uncover real needs, justify with conviction, and ship solutions that move metrics.Note: We will finish on April 21st. This gives you time to run interviews and synthesize together.Why I built this:I scaled a 0-to-1 energy product from 30K to 1M customers in 12 months at Oracle Energy &amp; Water by running discovery sprints. Got promoted to Principal PM and became the company's discovery lead. Now, I run my own Fractional Head of Product practice for Silicon Valley startups. Discovery has been my career differentiator.

Master AI-Powered Discovery. Build What Customers Need.

Master Fundamental Discovery Skills

Become a Discovery expert at your company

Ship a market leading product

You will be interviewing Customers in the course. This is a critical skill in Discovery, not to be outsourced to AI.

Must be able to schedule at least 1 Customer Conversation

Product Managers at a company without a structured discovery practice

Founders who need validation before investing time and money in product development.

UX Researchers who are overloaded with discovery work and are looking for a system to speed up their workflows

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

Cohort 1

Product Innovation & AI Trainer

Capital One

Cisco

Wesco

Google

Valerio Zanini

Product Management and Innovation trainer. Author, "AI for Product Managers".

Cohort 2

Discover opportunities with AI → validate with interactive prototypes → design AI features → automate workflows → ship functional software

Product Design Leader

Payoneer

Anna Arteeva

Product Design Leader and AI educator

Product Leader

Julia Bastian

Product Lead - Innovation & GenAI, ex VP of Product at Alasco

Senior Solution Architect, MBA

Vlad Daskalov

MBA, Agentic AI advocate, Senior Solution Architect

In an AI-accelerated product world PMs are expected to explore, ideate and validate ideas quickly, collaborate effectively with designer and developers whose roles are changing too.You'll learn from three experts with different backgrounds: Product, Design, and Engineering. This ensures you get deep insights into design and engineering topics while learning to navigate the change and bring your cross-functional partners along.<h3>What is covered:</h3><ul><li>AI for modern discovery and synthesis</li><li>Building apps and prototypes with prompt-to-code tools</li><li>Frontend basics</li><li>Essentials of app architecture: Backend, Frontend, Data, APIs</li><li>Working with existing assets: brand styles, design systems, open source code</li><li>Automation and integration with product workflow (Make, n8n, webhooks).</li><li>AI-powered functionality with integrated LLM, image and voice models</li><li>System prompts engineering basics for AI features</li><li>Analytics and idea validation so you can back up your prototypes with evidence.</li></ul>Then will talk about real hard topics<ul><li>cross-functional team collaboration</li><li>code hand over</li><li>work inside an existing codebase.</li></ul>❤️ Lovable Pro is included! Principles learnt are transferable to other tools

Learn the new PM stack: vibe-coding, automation, AI features, and code handover

AI-powered discovery and opportunity framing

Vibe-coding fundamentals and AI ecosystem

Frontend foundations and system architecture

Design systems and brand-consistent UI

Architecture, data, and automation

AI features, validation, and handover

You can clearly define problems, users, and desired outcomes

Product fundamentals

Familiarity with digital products and curiosity about how they work will help you get more out of the course.

No previous coding experience required

You should be comfortable with how digital products are planned, built, and shipped, and have working knowledge of the modern tech landscape

Understanding the tech company ecosystem

Product Managers, Owners, Researchers, Growth who want to become full-stack builders, validate ideas with confidence and iterate faster.

Non-developers across the organisation – sales, marketing, ops, GTM, finance, or HR – who want to build their own tools and experiments

Leaders in tech companies who want to make their teams more effective through AI coding, shape AI strategy, and sharpen workflows.