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N2· Engineering: product, sales and operations roles

Solutions & Sales Engineering with AI

You learn to research a prospect, run a discovery call, give a demo that answers their real problem, and prove the integration works, with AI doing the legwork and you doing the thinking.

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Who it is for
ECE, CSE and Mech students who like technology and people in equal measure and want to be the engineer in the room when a customer decides.
AI core
9 units · 20 h
This course
6 modules · 12 lessons · 3.2 h
Live projects
2, on Professional and Career
01Roles it prepares you for
  • Pre-sales Associate
  • Solutions Associate
  • Technical SDR

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

02Tools you will use
  • Perplexity (free)Free tier
  • Claude (free plan)Free tier
  • Google SheetsFree tier
  • HubSpot free CRMFree tier
  • n8n Community Edition (Saarthi-hosted)Saarthi sandboxVerified
  • Saarthi buyer role-play (voice)Saarthi sandbox
  • Saarthi sandbox (anonymised seller data pack + MCP server)Saarthi 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 · Solutions & Sales Engineering with AI

01What solutions engineers do2 lessonsThe sales cycle from the engineer's seat, technical credibility, and the ethics of never overclaiming.
  1. The engineer in the sales room8 min
  2. Lab: learn the product like a buyer would20 min
02AI prospect research and the ideal customer2 lessonsDefine who to sell to, research accounts with sources you can stand behind, and write outreach that respects people and the law.
  1. ICP, account research and respectful outreach8 min
  2. Lab: research five accounts and write first messages20 min
03Discovery calls2 lessonsAsk questions that uncover the real problem, put a rupee value on it, and take notes with AI without losing accuracy.
  1. Discovery: find the pain and price it8 min
  2. Lab: a voice discovery call with Saarthi25 min
04Demos that land2 lessonsBuild a demo story from discovery and show the product solving the buyer's problem on the buyer's kind of data.
  1. The demo is a story about the buyer8 min
  2. Lab: a seven-minute reconciliation demo25 min
05Integration proofs with n8n2 lessonsProve the product fits a buyer's workflow with a small, reliable automation, built with a human in the loop.
  1. Integrations buyers can trust8 min
  2. Lab: report to Sheets to alert in n8n30 min
06Architecture docs, RFPs and objections2 lessonsWrite the documents that get a deal approved, answer security and data questions accurately, and handle objections with evidence.
  1. Solution docs and security questions8 min
  2. Lab: solution document and questionnaire25 min
04Live projects

Two briefs. Real-shaped work.

  1. Project 1

    Discovery and live demo to a seller, graded on voice

    Saarthi plays the owner of a fictional Surat ethnic-wear business selling on Amazon.in and Flipkart (Tapti Tana Ethnic, a separate fictional profile in the sandbox profile pack). Research the account from that profile, run a voice discovery call, then deliver a seven-minute live demo of Saarthi's reconciliation on the sandbox data of S-033 Phulkari Lane or S-001 Kesariya Threads, the nearest ethnic-wear sellers in the seller pack, matched to what you learned. You are graded on what you ask, how you quantify the pain, how honestly you handle limits and whether you secure a concrete next step.

    You hand in

    • Account research note with every fact verified against its source
    • Recorded voice discovery call (12–15 minutes) and a checked summary with quantified pain
    • Demo outline and a data sheet that reproduces every figure shown
    • Recorded seven-minute demo with objection handling
    • CRM entry and a follow-up email with a dated next step

    Data: Saarthi anonymised seller data pack (settlement, MTR, returns reports) for S-033 or S-001, plus the fictional public-style Tapti Tana profile (no Surat seller exists in the seller pack, so demo figures come from S-033 or S-001).. Reviewed by Saarthi against a published rubric, signed off by a mentor.

  2. Project 2

    Integration proof and solution architecture

    A fictional seller wants proof that reconciliation can fit their daily routine. Build an n8n flow that reads a marketplace settlement report, writes new rows to Google Sheets without duplicates, flags fee deviations and alerts a person for approval. Package it with a solution architecture document and a checked data and security questionnaire.

    You hand in

    • Exported n8n workflow (credentials removed) running on the Saarthi-hosted instance
    • Test evidence: double-run with no duplicates, broken-file error alert, three hand-made transform test rows
    • One-page runbook
    • Solution architecture document (2–4 pages) with labelled data-flow diagram and responsibilities table
    • Completed ten-item questionnaire with library citations and routed 'needs owner' items

    Data: Saarthi sandbox: anonymised settlement CSVs (including one deliberately broken file), the data pack's fee rate card, and a fictional vendor's approved answer library.. Reviewed by Saarthi against a published rubric, signed off by a mentor.

05Practise out loud

In voice mock interviews and client calls, Saarthi plays: Rakesh-bhai, the fictional owner of a mid-size Surat ethnic-wear business selling on Amazon.in and Flipkart, takes a 20-minute discovery-and-demo call between packing shifts. He speaks Hinglish, was burned by a reconciliation tool that 'showed nothing useful', and interrupts with 'kitna paisa bachega?' and 'mera Flipkart wala data bhi chalega?'. He will only agree to a next step if you quantify his problem in rupees and show it on his kind of report.

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

06Enrol

Pick a plan for Solutions & Sales Engineering with AI.

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