I'm a product leader who loves taking products from 0→1 and helping companies reach product-market fit. Over the past decade I’ve built B2B SaaS in fintech, edtech, and platform ecosystems, from early startup through IPO.
Even after years of working with engineers (and even having a GitHub account) I had never shipped a line of code. I was intimidated by the terminal, afraid of breaking things, and convinced real coding required a CS degree.
AI-powered development tools changed everything.
Using AI tools, I shipped my first production app and finally understood how the pieces fit together. This workflow taught me the mental models I’d been missing.
That shift led me to start Fractions, where I help non-technical operators become builders.
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🔗 LinkedIn (100k+)
🤝 Coaching
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Marily is also an Executive Fellow at Harvard Business School where she teaches AI Product Management.
She has taught over 8k students on Maven and offers these courses:
✉️ hello@aiproduct.com
Reach out for corporate trainings and group/student discounts.
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Chatting endlessly with an “AI intern” instead of designing the context with clear principles.
Blaming “hallucinations” when the real issue is poor orchestration.
Trying to run an entire project from a single, overloaded chat window.
Treating AI like witchcraft and prompt spells instead of engineering.
AI gets better every day. But when it’s time to ship something serious, you don’t yet have a reliable way to make AI show up for you.
The problem isn’t AI. It’s how you’re using it.
This course exists for that exact gap.
AI is a new computing paradigm. To use it well, you have to:
Unlearn old patterns
Install new mindsets and habits
Build a meta-learning system that can carry your career for the next 20 years
That's hard, and we take it seriously.
This course is designed to teach you how to fish. On top of lessons and projects, we built two unique tools:
A build platform that consolidates key APIs and lets you deploy your projects with one command—so you can build fast, not fight boilerplate.
A lifetime community where you can share projects, ask questions, and get unstuck long after the course ends.
The end of our course is the beginning of your learning, and we will be with you.
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Shane Butler is a Principal Data Scientist at Ontra, where he leads AI evaluation strategy for product development in legal tech. He has 10+ years of experience in product data science, causal inference, and measurement across both B2B SaaS and consumer products, with prior roles at Stripe, Nextdoor, AppFolio, and PwC. His work focuses on practical, end-to-end methods for evaluating AI features in production, connecting offline quality signals to real user and business outcomes. Shane is also the co-host of the AI podcast Data Neighbor, where he interviews product, data, and engineering leaders shaping the next generation of analytics in an AI-driven landscape.
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She has built and led data science and product analytics teams at Microsoft, eBay, Nextdoor, and Superhuman (prev. Grammarly), working closely with product, engineering, marketing, and leadership. Her expertise spans experimentation, metrics design, modeling, analytics, and translating complex user behavior into clear, actionable insights.
Sravya is known for mentoring data scientists and non-data partners to think analytically, asking sharper questions, interpreting results with confidence, and making decisions even when data is imperfect.
In this course, she brings real-world, big-tech analytical frameworks, adapted for modern teams using AI as a copilot.
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What sets Hai apart: he has mentored hundreds of non-data professionals to ask better questions, interpret results confidently, and make decisions without waiting for an analyst.
This course brings FAANG-level analytical frameworks to students ready to think independently and move fast with AI as their copilot.
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As AI reduces the value of deep domain silos, the people who thrive will be the ones who can work across disciplines and ship.
Analytical independence - the ability to validate your own ideas and make data-informed decisions - remains the missing skill in most builders' toolkits.
AI can conduct the analysis, but it can't tell you what to ask or whether the answer makes sense. That requires analytical judgment.
This course teaches you to think like a senior Product Data Scientist. You'll learn the frameworks used at FAANG companies to frame problems, choose the right metrics, diagnose root causes, execute the analysis, and turn insights into decisions.
-> Join AI Builders Slack Community!! <-
What makes this different: No SQL. No stats lectures. Five weeks of hands-on real scenarios. You'll build end-to-end, metric specs, deep dives, experiment plans, stakeholder readouts.
The result: You become analytically self-sufficient. The last dependency removed from your toolkit. Make data-informed decisions in hours, not weeks.
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Ten years ago I started at Google and Airbnb. More recently, I was at Phantom shipping the safety & authentication layer that millions of users rely on. Across all of it, my focus has been the security, infrastructure, systems that run at scale without falling over.
That's the lens I bring to AI. We help founders and GTM leaders build practical AI systems that ship. Consulting, implementation, and workshops. I handle the architecture side: agent systems, MCPs, guardrails, the parts that make AI dependable enough to run a real business on.
Mika and I run King's Cross Labs on the same stack we build for clients. Every tool, every workflow, every agent is battle-tested in our own company first.
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Overwhelming. Where do you even start?
Noisy. Every week there's a new tool, a new tutorial, a new \"best prompt ever\"
Time-consuming to figure out alone
Frustrating. You know Claude should be saving you hours. But it still doesn't quite get you.
We've spent 1,000+ hours learning (and failing) in Claude so you don't have to. We've built and shipped software used by millions, and we've sat on both sides of the table: technical and non-technical. We built our own AI-native operating system from scratch. This workshop is the shortcut we wish we had.
In one day, you'll learn more than most people piece together over MONTHS of trial and error.
By the end of this workshop, you will have:
✅ A working AI agent crafted for your specific role and workflows
✅ Your own CLAUDE.md and context files — the \"brain\" that makes Claude actually know you
✅ A custom skill built for your needs
✅ Connected tools or MCPs so your agent can act
✅ Frameworks and mental models to keep building on your own
This is a hands-on build session, with instructors live in the room. not a passive webinar. We keep cohorts small and intimate. Spots are limited.
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Creator of the Unified Personality Architecture: Co-developed a statistically rigorous framework with Prof. Utho Creusen to translate complex psychometrics into a single actionable scale.
Enterprise & Private Equity Coach: Successfully implemented performance and M&A integration frameworks for high-stakes clients including Airbus, Daimler, and msg.
Host of the Stärken Snack Podcast: A leading thought leader broadcasting regular insights on data-driven leadership, psychological safety, and cognitive diversity.
You cannot fix burnout by working harder. You have a matching problem.
AI is making your team's hard technical skills obsolete faster than they can learn them. You cannot fix this \"AI anxiety\" or burnout by asking them to work harder. You don't have an effort problem; you have a matching problem.
Most Engineering Managers spend 70% of their week trapped in the \"Mediocrity Loop\" - refereeing personality clashes, fixing broken handoffs, and watching their team's shared knowledge collapse as junior roles vanish. You're bleeding runway and morale.
This 30-day accelerator gives you the system to break out. Using the Big Five (or CliftonStrengths) assessment, a proven framework, and the Strength Hack AI, you'll map your team's cognitive architecture and engineer the conditions for psychological safety - not just hope for it.
In 4 weeks, you will:
Stop Generalist Exhaustion: Identify energy leaks and delegate based on Cognitive Fit, not calendar space.
Engineer Swift Trust: Use the 6-dimension Matching Compass to translate friction into synergy.
Drive ROI: Transition from a reactive referee to a strategic orchestrator
The Overwhelmed Engineering Manager / Tech Lead
You lead a hybrid or remote team. You want a data-driven system, not another workshop.
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