Sarah Anto

Why No One Understands What You Built

Techstars

Y Combinator

Conception X

Deeptech Operator who scaled $1M→$30M

See before/after pitch rewrite, why starting with your tech instead of the customer's problem loses the room every time

Spot the #1 mistake that kills deep tech pitches

Walk through live exercise that strips away jargon and surfaces the business outcome buried inside your tech explanation

Find your real pitch in 30 seconds with the "So What?" test

See why most deeptech founders pitch information in the wrong order, and the simple re-order that makes investors lean i

Learn the 5-question structure investors actually follow

Two related skills in one course: master tech to speak the same language with your team. Use it to AI-prototype features or a side project.

Lead PM @ Booking.com, PhD

Vladimir Kalmykov 

PhD Computer Science, first Tech PM in Booking.com, author at ProductDo.io 

Jan'25

Cohort April'26

✅ Why invest in learning with me?I’m a Lead PM at Booking.com, and one of the first tech PMs there, with over 10 years in the field.Before moving into product, I was a Software Developer and earned a PhD in Computer Science. I’ve worked on both sides and know exactly what technical understanding PMs need - and don't.I'll teach you exactly what matters (and why) for driving products forward. You'll get the technical and AI-building fluency needed to drive your team, no coding, no database internals, no load balancers.✅ What can better technical understanding do for your career?From a survey of 650 PMs, 56% want to speak the same language as their engineers to communicate effectively, and build trust.61% want to estimate features on their own, so they can plan better and deliver on time.And today, technical understanding also lets you quickly AI-prototype features (43%) to show it to real users. In return, AI-building allows you to better understand Tech.Finally, if you want to land a Big Tech PM role, tech skills are critical.✅ What makes this course different?The course is 20% theory and 80% hands-on:&nbsp;you’ll do over 200 exercises / 8 projects, because that’s how real skills stick.

The technical understanding a successful PM needs - nothing more.

Gain tech fluency to lead your team effectively

Gauge feature complexity without devs and write solid PRDs

Prepare to handle technical interviews

Turn ideas into clickable full-stack prototypes or even start a side-project

The course is designed to explain the tech foundations and AI-building from the first (intuitive) principles.

No prior tech or AI experience needed

Senior Product Managers who want to level up their technical acumen

Jr/Middle Product Managers who want to lead with confidence and accelerate their growth

Program/Project Managers, Producers, Designers, Data Analysts, because tech foundations are the same for everyone

Develop the rare skill of listening to what your market needs but can't yet name — so when you make decisions, you're just right.

Cohort 7

AI Research Leader •Ex-Meta, Uber, Apple

Uber

Apple

Google

Canvas8

Abi Awomosu

AI Research Leader • Ex-Uber, Meta •  Bestselling Author of 'How Not to Use AI'

Cohort 6

Cohort 8

Most leaders don’t struggle with access to ideas or data. They struggle with knowing what matters before it’s obvious or too late.Most AI research courses teach extraction: summarize quicker, automate the asking, replacing the human with the synthetic.The Billion Person Focus Group® does the opposite. You use AI as a listening partner to access patterns from places where people actually gather and speak unfiltered— forums, communities, support tickets, sales calls, product data.Triangulate across sources. Bring receipts. Then hand off what you find to surveys, interviews, or experiments.Discovery first. Validation second.This isn't "move fast and break things." It's see first—act once.In two days, you’ll apply this to a real high-stakes decision and leave with:<ul><li>Visual market landscape maps </li><li>3–5 decision-ready hypotheses</li><li>A ready-to-run Listening OS — agents, workflows, cookbooks — customized to your market</li><li>A validation plan you can execute Monday</li></ul>And you keep everything — for the next launch, the next client, the next pivot. Stop renting insights. Start owning the capability.

See what your market really needs—before you build, launch, or scale. 

See your market as it actually exists— not how dashboards flatten it

Identify emerging market trends before they become mainstream.

Discover  the 'unknown unknowns' — what your market feels but can't say

Assemble AI advisors that shape decisions  — not yes-machines who confirm

Move at AI speed without losing the human meaning in the data

Stop renting insights or more AI tools — develop internal intelligence you keep

The course is taught primarily using Claude, but the methodology works across platforms. No technical skills required.

Familiarity with AI tools — you've used ChatGPT, Gemini, Claude or similar. 

Strategic Leaders (Product, Marketing, Strategy Leaders, Consultants) who need to spot opportunities before competitors or de-risk big bets

Founders, Entrepreneurs or Innovators who want to stop guessing at product-market fit and meet needs that actually exist

Senior Practitioners (Designers, Marketers, Strategists, Researchers) who want to ground their work in real signal — not assumptions

Go from undervalued designers who speak design to  strategic design partners who can speak business

February Cohort

Medium.com's Top Design Writer.

Kai Wong

Medium's Top Design Writer| 13 Years Designing in Low Maturity Organizations

January Cohort

March Cohort

When a CEO asks "What are you working on?", can you answer without design jargon?Design often doesn't have a skill problem. It has a translation problem.You do great work but explain "reduced cognitive load" instead of "40% lower bounce rate"—and executives tune out.They don't see value. They see cost and wonder if AI can do it cheaper.You don't need an MBA. You need frameworks that translate the work you're already doing.Data-Informed Design gives you those frameworks, backed by 27 design leader interviews from Target, Ford, Mastercard, Meta, Amazon, and more.What design leaders say:"Talk the same language. Learn how to talk the way they're going to understand." — Principal Design Consultant"Communication is a skill designers need even more than Figma. Anyone can pick Figma up—which is why the floor keeps rising." — Design Director, ex-Amazon"Even AI can do decent design drafts. What I want to see is: can you create impact?" — Head of Design, Enterprise"Every business function is hired to either increase revenue or reduce cost. Without a metric, design isn't mission critical." — Senior Design LeaderBring a case study. We'll transform it together.

In 4 weeks, You'll Learn How to Translate Design Work into Business Outcomes.

The ladder technique: How to justify design value

 Goals-Signals-Metrics Framework 

Problem Framing Mastery and Data Viz

The 5-minute story: the Presentation Framework that drives Action

Designers who want to use data to bypass office politics and prove their value immediately

Designers tired of watching 'strategic' roles like PMs get promoted while their insights are ignored

Designers in low-UX maturity environments where relationship-building isn't enough

Learn to spot weak value propositions early. So you build products users actually adopt, retain, and pay for, even in an AI-driven world

Product leader; Advisor, 

Amazon

Intuit

PayPal

PropertyGuru

Viveck P Kumar

Product leader with 20 years building and scaling consumer digital products

Cohort 1

Most products don’t fail because of poor execution. They fail because teams choose the wrong value to deliver.In my career, I’ve repeatedly seen smart teams:<ul><li>Solve real problems</li><li>Build well-designed products</li><li>Ship faster than ever</li><li>Still fail to gain adoption, retention, or pricing power</li></ul>The root cause is almost always the same: a weak or misaligned value proposition.AI has made this problem worse, not better.Today, teams can prototype in days, add intelligence to features, and ship at unprecedented speed. But AI doesn’t fix unclear value, it amplifies it. Products feel impressive in demos, yet confusing or unnecessary in real life.The deeper problem is that “value proposition” is taught as a slogan or a pitch, not as a thinking skill.There is no shared language or structured way to reason about:<ul><li>What value actually acquires users</li><li>What value retains them over time</li><li>What value helps users escape existing habits and lock-ins</li></ul>This course teaches a practical mental model : the OPEN framework to help you see, evaluate, and design value propositions with clarity and confidence across consumer products, including those that use AI.Not how to build faster. But how to build the right thing.

How to sense product failure by its value proposition (in an AI world)

Diagnose a product’s value proposition in 15 minutes

Pick acquisition vs retention value and stop mixing the two

Design 'apparent' value to users that drives first-time conversion

Create value that overcomes their current choice of product/service

Build  value that anchors brand and indexes on long term

Evaluate AI features by user value, not capability

The material is advanced so this is not for product people who have just joined the industry.

Must be a practising craft actively for at least 3+ years

Product Managers/Sr PMs PMs who shape product direction and need sharper judgment on what value will actually drive adoption and retention.

Founders Founders deciding what to build next and wanting early clarity on whether a product idea has real value or hidden flaws.

Design and engineering leaders Leaders influencing product decisions who care about product success, not just features or execution quality