Staging environment

Product Engineering Foundations for Vibe Coders

Sash Mohapatra

AI Educator and Builder | Ex-Microsoft

Learn the product engineering principles every vibe coder eventually needs

You've built something real with AI coding tools. You've shipped it. And you hit the honest problem: you don't know what you don't know.

  • What are the three layers of your app - frontend, backend, APIs, databases - and how do they talk?

  • What's a data model, and why does every reliable product start there?

  • How do you test changes in dev before users see them in production?

  • Why does your agent keep forgetting context?

  • Which decisions are safe on instinct, and which cost you a weekend if you guess wrong?

These are the engineering questions nobody covers in a vibe coding tutorial. Product managers absorb them through proximity to engineers. Growth marketers, operators, designers, and business-background founders rarely get that proximity - but they need the same answers.

This workshop gives them to you.

You'll work with AI tools the way someone with engineering intuition does - understanding what you're building and spotting problems early.

One day. Four stages: THINK → MAP → BUILD → SHIP. You'll build a working app and a vocabulary that works with Replit, Cursor, Claude Code, or Lovable - the same process I use to ship Pollzy.

Workshop agenda

  • What product engineering principles unlock for non-technical builders

    Why product engineering principles lead to better outcomes | What they unlock: reliable, maintainable software | The four-stage framework you'll use today

  • THINK: From vague idea to a PRD your agent can use

    User journeys before features | Scope: must-have, nice-to-have, not-now | Plan mode with your AI agent | Writing a PRD your agent can use | Live : Walk through the sample app's PRD live

  • MAP: The architecture and data model, before any code

    Project anatomy: frontend, backend, database, API | Why backend-first ships faster | Data models: entities, fields, relationships | Design the sample app's data model live

  • Break

    Thirty minutes. Eat, stretch, step away from the screen.

  • BUILD: Scaffold your app with habits that make every step reversible

    Commit before every AI session | Rules files that give your agent persistent memory | Docs-as-code: agent maintains your PRD and build log | Live build: data → API → frontend → auth

  • SHIP: Environments, secrets, and the non-panic recovery playbook

    Dev, staging, production environments | .env and .gitignore secrets discipline | Issues as backlog, build log as changelog | Recovery moves: revert, checkout, redeploy | Live deploy to production

  • Q&A: Apply the framework to your own builds

    Bring your questions about your own projects | How the framework applies to your specific builds

  • Close: Applying the framework to your own codebase this week`

    Walk back through the four stages: what changed for you today | Your one commitment for tomorrow's own codebase | 4 templates you'll walk away with

Learn directly from Sash

Sash Mohapatra

Sash Mohapatra

AI educator & Builder | 20 Years in Microsoft in Customer engineering and Sales

Previously at Microsoft
Microsoft
See all products from Sash

Who this workshop is for

  • Non-technical founders building products on Replit, Lovable, or Cursor who have moved past the prototype stage.

  • Growth marketers, operators, and BD pros who've shipped internal tools with AI but hit walls maintaining or extending what they built.

  • Designers, customer success leads, and business-background builders using AI coding tools who want to understand the technical foundations.

What's included

Sash Mohapatra

Live sessions

Learn directly from Sash Mohapatra in a real-time, interactive format.

Lifetime access

Go back to course content and recordings whenever you need to.

Community of peers

Stay accountable and share insights with like-minded professionals.

Certificate of completion

Share your new skills with your employer or on LinkedIn.

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Frequently asked questions

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