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D2· Design: UI/UX, product, communication and interior

Conversational & AI-feature UX

You learn to design AI features people can trust: ones that show uncertainty honestly, fail gracefully, ask for consent properly and talk to users in Hindi, Kannada and Hinglish as naturally as in English.

Choose a planRead the syllabus
Who it is for
BDes UI/UX and product design students who want to design the AI parts of products: assistants, insights, recommendations and chat, not just the screens around them.
AI core
9 units · 20 h
This course
6 modules · 12 lessons · 7.5 h
Live projects
2, on Professional and Career
01Roles it prepares you for
  • Product Designer
  • UX Writer
  • Conversation Designer
  • Design Technologist

The skills these roles ask for. Preparation, not a promise of a job.

02Tools you will use
  • Claude (free plan)Free tier
  • ChatGPT (free plan)Free tier
  • Figma (Starter plan, AI credits incl. Figma Make)Free tierVerified
  • v0 by Vercel (Free plan)Free tierVerified
  • Google SheetsFree tier
  • Saarthi sandboxSaarthi sandbox

You never pay for a tool subscription. “Verified” means we checked the free access on the vendor’s own site this month. Tool names describe what you learn; no vendor endorses Launchpad.

03Syllabus

What you will learn, in order.

Lesson films are narrated with an AI voice, over visuals made with AI tools and checked by our team. Saarthi, the coach, is an AI. Mentors and reviewers are people.

Part 1 · The AI core, shared by every stream

00Set up your coach1 hLearn how the core works, write the learning-context document that tells every AI tool who you are, and set Saarthi up as a coach that makes you think instead of thinking for you.
  1. How this core works6 min
  2. Write your learning-context document8 min
  3. Seven roles for AI, and study modes7 min
01How LLMs work and fail2.5 hBuild a working mental model of a large language model: tokens, prediction, context windows and memory. Then learn its predictable failures (hallucination, sycophancy, stale knowledge, bad arithmetic) and reproduce them yourself.
  1. Tokens and next-word prediction7 min
  2. Context windows and memory7 min
  3. Hallucination, sycophancy and other failures8 min
  4. Lab: one prompt, three models, five failures8 min
02Description and context engineering3.5 hWrite briefs that get the right output the first time: role, task, context, examples and format. Then make them reusable with Claude and ChatGPT Projects, Gemini Gems, custom GPTs and NotebookLM, and learn to work with PDFs, spreadsheets and images.
  1. The brief: role, task, context, format8 min
  2. Examples and output formats7 min
  3. Projects in Claude and ChatGPT8 min
  4. Gems, custom GPTs and NotebookLM8 min
  5. Working with files: PDFs, spreadsheets, images8 min
03Verify everything2.5 hCheck AI output the way fact-checkers do: lateral reading, tracing citations and numbers to the original, using deep-research modes without trusting them blindly, and testing a prompt properly with a 10-case golden set.
  1. Lateral reading7 min
  2. Checking citations and numbers8 min
  3. Deep-research modes: use and limits7 min
  4. Your first eval: a 10-case golden set8 min
04Connectors and MCP2 hConnect AI to the places your work lives (Drive, Gmail, Sheets, business data) without writing code. Learn what an MCP server is, why a reviewed directory differs from unreviewed community servers, how to grant the least access that works, and how to keep browser extensions on a short leash.
  1. What connectors and MCP are8 min
  2. Trust, least privilege and the reviewed directory8 min
  3. Browser extensions and AI browsers7 min
  4. Lab: ask the seller-data MCP server, check every answer8 min
05Agents and automations3.5 hHand multi-step work to AI safely. Tell an agent from an automation, decide what to delegate, use browser and coding agents with care, and build an n8n workflow that uses AI with a human-approval step before anything leaves the system.
  1. Agents vs automations: what to delegate8 min
  2. Browser agents, safely7 min
  3. Automation basics with n8n and Zapier8 min
  4. Lab: build an automation with a human-approval step8 min
  5. Failure modes and your failure-mode note7 min
06AI for learning and careers1.5 hUse AI to learn faster without outsourcing the learning, write applications that still sound like you, and practise interviews out loud with Saarthi.
  1. Learning with AI, not instead of learning7 min
  2. Applications in your own voice7 min
  3. Mock interview with Saarthi8 min
07Diligence: law, ethics, integrity2.5 hThe rules that apply when you use AI in India: the DPDP Act 2023 and its 2025 Rules, academic integrity and disclosure, copyright (including where Indian law is still unsettled), and bias. You finish by writing your own AI-use policy.
  1. DPDP Act 2023: personal data and AI8 min
  2. Academic integrity and disclosure7 min
  3. Copyright and AI in India8 min
  4. Bias and fairness7 min
  5. Write your personal AI-use policy7 min
08Core capstone1 hPut all four Ds together on one anonymised marketplace settlement file: ask good questions, automate one step, verify every number against Saarthi's P&L engine, and defend your work live in five minutes.
  1. The capstone brief6 min
  2. Lab: ask, automate, verify8 min
  3. Prepare your 5-minute defence7 min

Part 2 · Conversational & AI-feature UX

01What makes AI features different2 lessonsProbabilistic outputs, shifting mental models, and the established guidelines for human-AI interaction.
  1. Designing for a system that is sometimes wrong22 min
  2. Lab: teardown of three AI features45 min
02Uncertainty, errors and recovery2 lessonsShow confidence and evidence honestly, design every failure state, and give users control.
  1. Showing uncertainty without scaring people24 min
  2. Lab: a state matrix for an AI insight card50 min
03Consent, data and trust2 lessonsDesign consent that is specific and honest under India's DPDP Act, and make AI content clearly labelled.
  1. Consent and transparency people can understand22 min
  2. Lab: consent and AI-settings screens in three languages45 min
04Conversation design fundamentals2 lessonsIntents, turns, repair and persona, and how to turn a conversation spec into a system prompt.
  1. Conversations are flows with words24 min
  2. Lab: spec, system prompt and ten test dialogues55 min
05Indian-language conversation design2 lessonsDesign for Hindi, Kannada and Hinglish: script, register, numbers, code-mixing and testing with speakers.
  1. Hindi, Kannada and Hinglish are design decisions25 min
  2. Lab: Kannada and Hindi flows with failure states55 min
06Prototyping and evaluating AI features2 lessonsWizard-of-Oz tests, prompt prototypes and small evaluation sets that keep AI features honest.
  1. Test the AI behaviour, not just the screens22 min
  2. Lab: a 30-case evaluation of the returns insight60 min
04Live projects

Two briefs. Real-shaped work.

  1. Project 1

    Saarthi returns-insight feature, end to end

    Design an AI feature for Saarthi that tells an Indian marketplace seller why their products are being returned and what to do about it. Cover discovery, consent, every state of the insight including uncertainty and errors, the correction loop, and an evaluation of the AI behaviour on synthetic data.

    You hand in

    • Feature definition: inputs, outputs, who decides what, success measures
    • Consent and AI-settings screens with layered notices
    • Insight component with at least ten designed states and a clickable correction loop
    • Prompt prototype and a 30-case evaluation with two rounds of scores
    • Usability test with three to five seller-like participants on the prototype
    • Ten-minute presentation covering decisions, risks and what to monitor after launch

    Data: Saarthi sandbox synthetic returns data shaped like Saarthi's returns tables: orders, return reasons, free-text comments in English and Hinglish, product listings and dates. Fully synthetic; no real seller data.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

  2. Project 2

    Kannada and Hindi shopping-assistant flows with failure states

    Design a shopping assistant for a fictional Indian D2C home-goods brand that serves customers in Kannada, Hindi, Hinglish and English. Deliver a spec, a working system-prompt prototype, complete flows with failure states in each language, and evidence from native-speaker testing.

    You hand in

    • Conversation spec: purpose, persona, intents, slots, confirmation, repair and escalation rules
    • System prompt prototype with the synthetic catalogue
    • Flow maps for find-product and start-return with at least four failure branches each
    • Chat screens in Figma for Kannada and Hindi, including quick replies and human handoff
    • Language QA sheet reviewed by native speakers
    • Test report from at least four native-speaker sessions with unexpected inputs logged

    Data: Saarthi sandbox synthetic catalogue of 40 home-goods products with prices, colours, stock and a returns policy, plus synthetic order records for return scenarios.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

05Practise out loud

In voice mock interviews and client calls, Saarthi plays: Arjun, a product lead at an Indian seller-tools startup, about to ship an AI returns-insight feature. He is excited about the model and worried about support tickets. He asks what happens when the AI is wrong, how sellers will know, and whether your Kannada flows were tested with anyone who actually speaks Kannada.

On plans that include mock interviews. You get written feedback after every call.

06Enrol

Pick a plan for Conversational & AI-feature UX.

One payment. The access deadline for each plan is shown before you pay.

  • Foundation

    01

    Learn the AI your field now runs on.

    ₹2,999

    One payment. GST included.

    • Access for 120 days (about 4 months) from the day you pay
    • No 1:1 mentor sessions
    • The common AI core and your domain course
    • Saarthi, your AI coach, any hour
    • Hands-on labs on free tools
    • Verifiable certificate
    Enrol on Foundation

  • Professional

    02

    Prove it on real work.

    ₹7,999

    One payment. GST included.

    • Access for 180 days (about 6 months) from the day you pay
    • One 1:1 session with a mentor
    • Everything in Foundation
    • Two live projects, reviewed by Saarthi and a mentor
    • Public portfolio page of verified work
    • Voice mock interviews
    • One 1:1 coaching session
    Enrol on Professional

  • Career

    03

    Work alongside our team.

    ₹14,999

    One payment. GST included.

    • Access for 240 days (about 8 months) from the day you pay
    • Four 1:1 sessions with a mentor
    • One 1:1 call with an industry expert
    • Everything in Professional
    • Four-week supervised practicum with the Saarthi team
    • Four 1:1 coaching sessions with your mentor
    • An exclusive 1:1 call with an industry expert in your field
    • CV and LinkedIn review
    • Priority mentor replies
    Enrol on Career

Your access period starts the day you pay and is shown before you pay. One exam pause per enrolment, for up to 15 days. When access ends the course locks, and your portfolio page and certificate stay live. Full refund within 7 days, pro-rata after that, and an automatic refund for any practicum, 1:1 mentor or expert session we do not deliver. Refund policy