Log in

Become an AI-Native Leader

Build an AI-native operating model that ties automation to revenue, reduces decision bottlenecks, and turns team knowledge into reusable workflows and shared context.

  • Intermediate
  • 19 lessons
  • 2 hr 23 min
  • Taught by Lauren Vriens
Watch with Pro

What you'll learn

  • Measure AI by Business Impact Tie AI initiatives to revenue, retention, margin, cash flow, or throughput instead of generic productivity gains.
  • Prioritize Revenue Workflows Find the bottlenecks, handoffs, and translation loss that slow customer value, then apply AI where it improves flow.
  • Build Shared AI Context Create reusable markdown files, instructions, and shared context systems that keep people and AI working from the same source of truth.
  • Productize Repeatable Work Design repeatable AI jobs, skills, and agents around clear outcomes, constraints, inputs, tools, and success criteria.
  • Lead AI-Native Teams Set operating principles, review rhythms, and adoption rituals that make AI useful without flooding leaders with low-value output.
  • Improve AI Output Quality Use AI to surface assumptions, ask better questions, organize knowledge, and turn repeated corrections into stronger workflows.

Lessons 19 lessons · 2 hr 23 min

Every lesson comes with Pro, $29 a month.

Revenue-Driven AI Leadership 53 min

  1. Lesson 1: Introduction and Background 5 min
  2. Lesson 2: AI's Shift From Productivity to Revenue 12 min
  3. Lesson 3: Theory of Constraints and Finding Bottlenecks 12 min
  4. Lesson 4: Applying AI to Revenue-Critical Workflows 14 min
  5. Lesson 5: Teaching AI to Learn You 11 min

AI-Native Operating Models 44 min

  1. Lesson 6: The AI Paradox and Slowing Decision Velocity 3 min
  2. Lesson 7: From Slop Workers to Iterators and Productizers 9 min
  3. Lesson 8: Measuring AI Impact and Reducing Translation Loss 10 min
  4. Lesson 9: Swarm Thinking, Shared Principles, and Multiplayer AI 11 min
  5. Lesson 10: Markdowns, HTML, and Shared Context Systems 7 min
  6. Lesson 11: AI Operating Principles and Team Adoption Tactics 4 min

AI-Native Team Workflows 47 min

  1. Lesson 12: AI Onboarding: Access, Context, and Jobs 4 min
  2. Lesson 13: Markdown Files, Skills, and Connectors 7 min
  3. Lesson 14: Memory, System Instructions, and Personal Context 7 min
  4. Lesson 15: Principles for Better AI Outputs 7 min
  5. Lesson 16: Second Brain and Knowledge Organization 5 min
  6. Lesson 17: Skills, Agents, and What Good Looks Like 6 min
  7. Lesson 18: Practical AI Workflows for Teams 8 min
  8. Lesson 19: AI Roles, Interns, and the Future of Work 4 min

Your teacher

Lauren Vriens

Co-Founder and Chief Product Officer

Lauren Vriens is Co-Founder and Chief Product Officer of a startup driving enterprise growth by harnessing the intersection of human judgment and AI systems. Previously, she created Accenture's first enterprise GenAI product (now a $340M business) and scaled an electric vehicle startup from $0 to $50M in 18 months. She has advised executives at FINRA, Waymo, and Stripe on transformation in an AI-native world, and her insights on AI have reached over 25M people. A Fulbright Fellow who has spoken at TEDx, Extraordinary Women on Boards, Microsoft, JPMorgan, and a16z NY Tech Week, Lauren distills the pace of change into actionable clarity - drawn from real-world experience building what's next.

Related recordings

  2. Finally Getting AI to Do Real Work

    Learn why AI outputs still fail in everyday work, then apply durable habits for context, prompting, projects, and tool-connected workflows that make models useful for real documents, decks, research, and operating work.

    Nate Grahek Beginner · 8 lessons · 1 hr 11 min

  3. The Human-First Agentic Content Workflow Workshop

    Build human-in-the-loop n8n workflows that turn existing team knowledge into polished content assets while preserving brand judgment, approvals, and scalable publishing paths.

    Nate Grahek Beginner · 7 lessons · 1 hr 2 min