About the Curriculum
Every module, session, project, and milestone across both plans. Built for the next generation of AI-native product builders.
KICKOFF
DAY 1 - Cohort Kickoff
90 MINS · LIVE WITH RAJAT
Who is in this cohort and why it matters
How to get maximum value from Base
The product builder mindset on what shifts today
Module consumption guide: what to watch first
Community setup, accountability pods, daily prompts
Q&A and energy-setting for week one
Weeks 1 - 2
What Product Designers Actually Do
2 HOURS · 4 LESSONS
PM vs PD vs UX vs UI the real decision split in teams
How product decisions get made: startups vs scale-ups vs enterprise
The designer's seat at the table why most lose it and how to keep it
AARRR: the product lifecycle every designer must understand
Micro-exercise: map one app you use daily to its likely business model
Problem Discovery & Framing
2.5 HOURS · 5 LESSONS
User problems vs. feature requests why this distinction is everything
Jobs-to-be-done: the only framework you actually need
Research → Insight → Opportunity: how the chain works
Writing a problem statement that constrains and guides design
Micro-exercise: write a JTBD statement for your chosen project domain
Product Strategy & Metrics
2.5 HOURS · 5 LESSONS
North Star Metric: what it is, why it matters, how teams align around it
Input metrics vs. output metrics which designers can actually influence
Business model → product strategy → design decisions: the chain
Prioritisation basics: RICE and the opportunity sizing instinct
Case study: how Duolingo's streak metric shapes every design decision
Systems Thinking & User Journeys
2.5 HOURS · 5 LESSONS
End-to-end user journeys: from first touch to habitual use
Edge cases, empty states, and error states as design requirements
Platform thinking: iOS, Android, Web designing across surfaces
The feature lifecycle: onboarding → activation → retention → referral
Micro-exercise: map the full journey of one feature in your project product
Business of Design
1.5 HOURS · 3 LESSONS
Unit economics for designers: CAC, LTV, and why they shape UX
Growth loops and retention mechanics how design drives revenue
Reading a product brief and finding what is missing
Case study: how Zepto's dark store model determines checkout UX
Session 2: Product Thinking Debrief + Project Setup
3 HOURS · 1.5 HRS LEARNING + 1.5 HRS BUILD
Debrief on M01–M03: questions, misconceptions, real examples
Live teardown: apply JTBD + metrics to a well-known Indian product
Project setup workshop: every student applies the 3-filter rubric
Domain selection: fintech, health, edtech, B2B, consumer what each demands
Students leave with product chosen and JTBD statement written
AI-First Design Workflow
3 HOURS · 6 LESSONS
AI across the full design process where it helps and where it does not
Prompting for designers: research, ideation, critique, synthesis
AI-augmented user research: persona simulation, review mining, guerrilla synthesis
From research chaos to one insight statement using Claude
Building your personal AI design stack
Micro-exercise: run a 30-minute AI research sprint on your project product
Designing AI-Native Products
3 HOURS · 6 LESSONS
UX patterns for AI features: chat, agents, inline AI, ambient AI
Designing for probabilistic outputs when the AI is uncertain
Onboarding for AI products: setting expectations without killing trust
Case studies: Notion AI, Linear, Arc, Cursor what makes them work
Common AI UX failures and how to avoid them
Micro-exercise: audit one AI feature in any product for UX quality
Vibe Coding + Figma MCP
2.5 HOURS · 5 LESSONS
HTML and CSS literacy: what designers need to know and nothing more
Claude Code + Figma MCP: the pipeline from design to working component
Prototyping with v0, Lovable, Claude Artifacts when to use which
Prompting for a component vs. a full page vs. a complete flow
Connecting a public REST API to your prototype (live demo)
Micro-exercise: generate working code for one screen using Cursor or Claude Code
Session 3: AI Workflow Clinic + Build Kickoff
3 HOURS · 1.5 HRS LEARNING + 1.5 HRS BUILD
Debrief on M06–M08: questions, tool issues, prompt troubleshooting
Live demo: Rajat runs a full AI research sprint on a product live
Live demo: generate a working screen from a Figma frame using Claude Code
Project brief finalisation: every student locks problem statement + research plan
Build kickoff: students begin their AI-assisted research sprint in session
Students leave with research synthesis complete and problem statement locked
WEEKS 3-4
Session 4: Build Clinic - Research to Design
3 HOURS · 1.5 HRS LEARNING + 1.5 HRS BUILD
Each student shares research synthesis — Rajat gives live feedback
Common patterns: what insights are strong, what needs sharper framing
Live demo: move from insight to information architecture in 20 minutes
Workshop: students design first 2–3 screens of their project in session
Doubt block: tool issues, prompting challenges, scope questions
Students leave with IA mapped and first screens drafted
BUILD GUIDE
Feature-Level Design
SELF-PACED · STRUCTURED TEMPLATE
Step 1 : Choose: apply the 3-filter rubric to lock your product and feature
Step 2 : Research: 30-minute AI research sprint using Claude + Perplexity
Step 3 : Frame: write your problem statement using JTBD + metric
Step 4 : Map: IA and core user flow for the feature you are improving
Step 5 : Design: 3–5 key screens using Figma or AI-assisted tools
Step 6 : Build: generate a working prototype using Cursor or Claude Code
Step 7 : Test: run a 3-person guerrilla test or AI-simulated session
Session 5: Build Clinic — Design to Prototype
3 HOURS · 1.5 HRS BUILD REVIEW+1.5 HRS DOUBT
Each student presents work-in-progress: problem → insight → design so far
Structured peer feedback: what is the strongest decision, what needs rethinking
Rajat's model critique: one student's work dissected live for the cohort
Live demo: from Figma screens to working browser prototype in Cursor
Doubt block: code generation issues, API integration, design decisions
Students leave with prototype working and test plan ready
Project 1 Submission
END OF WEEK · ASYNC
Problem statement + JTBD framing
Research synthesis (AI-assisted, one-page insight doc)
3–5 designed screens with metric rationale
Working prototype (browser-ready or Figma with AI-generated components)
Lightweight test findings (3 users or AI-simulated session)
WEEK 5
What you walk away with
BASE GRADUATE · END OF WEEK 5
The product builder mental model: metrics, JTBD, business literacy, systems thinking
An AI-native research and design workflow you have actually used on a real project
One portfolio-ready case study: problem → research → design → prototype → write-up
Community access and peer network from the cohort
A clear, honest understanding of what Pro unlocks — and whether it is right for you
Case Study Anatomy : The Essentials
2 HOURS · 4 LESSONS
What a case study is actually trying to communicate (it is not a project diary)
The narrative arc: problem → insight → decision → outcome
What to show vs. what to hide — less process, more thinking
The Zomato teardown: a worked example of strong case study structure
Anti-patterns: the 5 most common Base-level case study mistakes
Session 6 (Final): Case Study Workshop + Cohort Presentations
3 HOURS · 1 HOUR WORKSHOP + 2 HOURS PRESENTATION
Case study writing workshop: students structure their Project 1 write-up in session
Rajat writes a mini case study live as a model — 20 minutes, real time
Cohort presentations: every student presents their project — 5 minutes each
Structured feedback format: one strength, one gap, one question from the cohort
Rajat's closing critique: patterns across the cohort, what to improve
Base graduation: what Pro adds, how to upgrade, what comes next
PLAN 02 - PRO
WEEKS 6-7
The 7-layer teardown framework used in Pro live sessions
Full Zomato teardown: worked example from brief to write-up
Case studies for hiring vs. for storytelling — different audiences, different structures
How to show product thinking, not just visual output
Anti-patterns: what kills a case study at the senior review stage
AI-assisted case study writing: prompting Claude to sharpen your narrative
Portfolio Framework
2.5 HOURS · 5 LESSONS
What product companies in 2026 actually look for in a portfolio
Narrative architecture: from hook to impact in 4 minutes
Visual craft — typography, grid, imagery, scroll experience
Portfolio platforms: Notion, Figma, web-based — pros and cons
The positioning question: what makes your portfolio different from the next 50
Micro-exercise: run a 30-minute AI research sprint on your project product
Hiring, Interviews & Positioning
2 HOURS · 4 LESSONS
How product companies hire designers in 2026 — what the process actually looks like
4 interview types and how to prepare for each
AI-augmented interview prep: simulate interviews with Claude
LinkedIn optimisation and inbound opportunity generation
Salary negotiation: using a product impact story, not a UI comparison
Pro Kickoff + Live Teardown #1
3 HOURS · 1.5 HOURS TEARDOWN + 1.5 HOURS BUILD
Pro cohort kickoff: what the next 5 weeks look like, capstone preview
How teardowns translate directly into case study structure
Project 2 brief: intro to the expanded scope — multi-journey feature design
Build block: students begin domain selection for Project 2
Live Teardown #2 + Project 2 Framing
3 HOURS · 1.5 HOURS TEARDOWN + 1.5 HOURS BUILD
Student-voted teardown: Zepto, CRED, Swiggy, or Spotify — deep systems + business model
Frameworks stress-tested across a different product type than Teardown 1
Project 2 framing workshop: problem statement + metric selection
Multi-journey scoping: how to scope something bigger than a feature
Students leave with Project 2 problem statement approved
Project 2 Research + IA Workshop
3 HOURS · 1.5 HOURS LEARNING + 1.5 HOURS BUILD
Live AI research sprint: Rajat models a full competitive + user research cycle
Journey mapping for multiple user types and entry points
IA workshop: every student maps core journeys for Project 2
Doubt block: scope decisions, metric framing, research synthesis
Students leave with IA + research synthesis complete
Project 2 Design Sprint + Critique
3 HOURS · 1.5 HOURS BUILD + 1.5 HOURS CRITIQUE
Design sprint: students build core screens of Project 2 using AI tools
Peer review pairs: structured feedback on design decisions
Rajat model critique: one student's work dissected live
Portfolio narrative workshop: structuring Project 2 as a case study while building
Students leave with 3+ screens designed and case study outline drafted
Project 2 Complete
END OF WEEK 2 · ASYNC SUBMISSION
Multi-journey feature design with 5+ screens across core flows
AI-assisted research synthesis + metric rationale
Working prototype (browser-ready) with one live data connection
Case study write-up: 7-layer structure, portfolio-ready
WEEKS 8-10
What you walk away with
DELIVERABLES
3 portfolio projects: Base project (feature-level) + Pro Project 2 (multi-journey feature) + Capstone (end-to-end product with working prototype)
Full AI-native workflow: research, design, code generation, API integration — used end-to-end across all three projects
Advanced skills: stakeholder management, technology literacy, communication, personal brand, interview positioning
Demo Day recording as a public portfolio asset
Hiring pipeline access: profile shared with partner companies, alumni network post-cohort
Capstone Kickoff + Scope Workshop
3 HOURS · 1.5 HOURS LEARNING + 1.5 HOURS BUILD
Capstone brief announced: end-to-end product design, multiple journeys, working prototype
How to scope an ambitious product without overcommitting
The v1 scope document: core journeys, key screens, metrics per journey
Capstone scoping workshop: every student's scope approved before leaving
Advanced topic intro: Stakeholder Management how designers influence decisions upward
Technology for Designers
1.5 HOURS · SHORT MODULE
What happens after design handoff which is the engineering reality
APIs, databases, and auth: what designers need to understand (not build)
Technical constraints that shape design decisions: latency, state, permissions
How to read a technical spec and ask the right questions
Working alongside engineers without slowing them down
Capstone Research Sprint + Build Start
3 HOURS · 1 HOUR RESEARCH + 2 HOURS BUILD
Live AI research sprint: 45 minutes of deep research modelled by Rajat
Synthesis workshop: turning research into a one-page product brief
Build block: students begin IA and first-level wireframes for capstone
Advanced topic: Product Management Basics: how PMs think, how designers can think like them
Students leave with research done and IA skeleton started
Capstone Design Clinic
3 HOURS · 1.5 HOURS BUILD + 1.5 HOURS CRITIQUE
Every student shares capstone progress: IA + first screens
Rajat's structured critique: product thinking quality, not visual polish
Workshop: AI-assisted screen generation for the core journeys
Advanced topic: Communication Skills for Designers presenting work to stakeholders
Students leave with core screens designed across all major journeys
Capstone Build Sprint — Prototype + Data
3 HOURS · 2 HOURS BUILD + 1 HOUR DOUBT
Build sprint: Cursor + Claude Code to generate working prototype
API integration: connect one public data source to the prototype
Designing for real data: loading, error, and empty states
Portfolio group reviews — Batch 1: first half of cohort presents progress
Students leave with working prototype and half the cohort reviewed
Personal Branding for Designers
1 HOUR · SHORT MODULE
Why personal brand is a career asset, not vanity
LinkedIn for designers: what to post, how often, what to avoid
Building authority through sharing work-in-progress publicly
Your positioning statement: one sentence that explains why you are different
Using your capstone as your first piece of thought leadership content
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