Admissions for 2027 intake is now open

AI First Learning

Learn AI by applying it to real business problems, building products, and shipping solutions.

A student asking a question with a microphone in a full Mesa session

The AI curriculum, in numbers.

  • 150hrs

    Of AI learning and building

  • 25+

    AI tools students get fluent in

  • 6

    Terms, from no-code to fine-tuning

  • 50+

    AI products launched by the Mesa students in year one

The Mesa approach to learning AI.

Students raising their hands in a Mesa class
  • Every Student Builds with AI

    Every student builds with AI, with projects tailored to their baseline and target role.

  • Business + Technical Mentorship

    Learn from both business and technical mentors at every AI workshop and hackathon.

  • Showcase Your AI Builds

    Present projects to external founders and operators every term. Top builds get featured publicly.

  • Feedback in 48 Hours

    Get actionable feedback on every submission within 48 hours.

Six terms, one path to your own AI product.

  1. Term 1

    Foundations of AI & No-Code Product Building

  2. Term 2

    Voice, Multimodal, and Agentic AI Products

  3. Term 3

    Vertical AI Products + Automation + Vibe Coding

  4. Term 4

    Fine-Tuning & Open Source AI Productization

  5. Term 5

    Building & Scaling AI Agents and Systems

  6. Term 6

    Thesis: Solve a Real Problem with AI

  7. The goal

    Launch publicly and reach 100 paying customers

    The thesis product goes live on Product Hunt and is pitched to investors.

AI Projects & Challenges

Every term ends in builds that are tested on real companies, real users and real revenue, plus a hands-on AI Building Test.

01
Case study

AI Integration Case Studies

Break down how a real company put AI into its product or operations, and what it changed.

02
2–4 weeks

Live Projects with Companies

Take a real brief from a partner company and hand back a working AI build.

03
Hackathon

Sectoral-Functional Hackathons

Build a working AI solution for one sector or function. A product, not a deck.

04
Challenge

GTM Challenges

Take an AI product to market: position it, price it and find its first users.

05
Challenge

What AI Features Would You Add?

Pick a product you use every day, then design and prototype the AI features it is missing.

06
Challenge

User Challenges

Put your build in front of real users, watch what they do and ship the fixes.

07
Challenge

Monetising Challenges

Turn a build into revenue, from pricing and a paywall to the first paying customer.

AI Masterclasses

Every term, founders and operators unpack real AI products, sharing how they're built, deployed, and scaled.

Students and a mentor walking through a product flow on a screen

Behind the Scenes of an AI Product

See how a live AI product really works, and what broke.

A student mapping an architecture on a whiteboard

AI Product Architecture Breakdown

Tear down a real AI product's stack and moat.

Two students working on laptops during a sprint

Voice AI Sprint

Build a working voice agent, from speech-to-text to speech.

A team presenting to the class

GTM for AI Products

Position and sell an AI product the AI-native way.

Students in a sales role-play around a table

Sales for AI Products

Handle AI objections and run a POC that closes.

Students listening during a masterclass

AIxSector Deep Dives

Find where AI is creating roles in finance, health, legal, ops and more.

Marquee Mentors

Operators who build with AI every day run the workshops, sit in on hackathons and judge the AI Showcase.

Explore workshops

Naveen Kumar Bhansali

Founder, BlitzAI

Naveen Kumar Bhansali
AI expertise

AI & Analytics Consultant with experience in applied AI and analytics; associated with IIM Bangalore.

BlitzAIIIM BangaloreDell TechnologiesInfosys

Blessin George Varghese

Seasoned AI Practitioner

Blessin George Varghese
AI expertise

Works with LLMs, conversational AI, and AI security, with experience exploring frontier AI technologies.

SRMHealthMicrosoftAdobe

Bhaskarjit Sarmah

Head of AI Research, Domyn

Bhaskarjit Sarmah
AI expertise

Leads financial AI research and mentors learners in Generative AI, LLMs, and machine learning.

DomynISBJohns Hopkins UniversityMITThe University of Texas

Vishal Gupta

AI & GenAI Product Leader, Haleon

Vishal Gupta
AI expertise

Builds and scales AI-powered products, from early-stage innovation to enterprise-level deployment.

HaleonIIFTXtelify

Harkirat Singh

Product Manager & GTM Lead, Zivy

Harkirat Singh
AI expertise

Builds technology products and supports AI founders through buildathons, product demos, and builder communities.

Aekyum

Dhruv Dhingra

Business & Growth Operator, Lokal

Dhruv Dhingra
AI expertise

Teaches practical applications of AI in business, growth, and operational decision-making.

KukuSwiggy

Tushar Nain

Product Lead, Grapevine

Tushar Nain
AI expertise

Built AI-powered hiring products, including a job discovery agent that reached 100K users.

GrapevineSattvaZinnovAshoka University

Mitul Aggarwal

Founder & Chief Architect, 302Labs

Mitul Aggarwal
AI expertise

Builds AI-powered business automation systems and has delivered AI training at Mesa School of Business and IIM Bangalore's NSRCEL.

302LabsNetcore

Divij Bajaj

Data & Applied Scientist, Microsoft

Divij Bajaj
AI expertise

Builds production-scale AI/ML solutions and award-winning AI agents, including an AI education copilot.

MicrosoftVMwareUniversity of Hyderabad

Sreeram Sridhar

AI Product Manager, Swiggy

Sreeram Sridhar
AI expertise

Builds enterprise GenAI products and agentic AI workflows for large-scale business operations.

SwiggyIVCAPeople+aiPaytm

25+ AI tools. The stack real startups run on.

Students get fluent in the tools AI-native teams use every day, from no-code builders to agent frameworks. The stack is reviewed every cohort.

BYOP: Build your own product

Build a full-stack AI product in 8 weeks.

For those looking to move closer to technology and into AI-first roles. Build and deploy a real AI product, test it with real users, measure its impact and develop a business model to monetise it, creating proof of work for your next role.

Judged at the AI Showcase by outside founders and operators

  • Build
  • Deploy
  • Real users
  • Monetise
A student presenting her product to the room
  1. Step 01

    Scope

    Pick a problem you have seen yourself: at work, in an internship, or in your BSL project.

  2. Step 02

    Build

    Design the workflow, add a simple front end and a database.

  3. Step 03

    Ship

    Deploy it as a live link anyone can open.

  4. Step 04

    Get users

    Find real users. Report what worked, what broke and how many used it.

  5. Step 05

    Monetise

    Work out how it could earn, and present the business model.

From the BYOP sprints

Three BYOP winners holding their prize cheques
Pitch day

BYOP pitch day

Cash prizes for the top AI products of the sprint.

The winning team holding a Mesa winner cheque with mentors
Year one

50+ AI products launched

By Mesa students in their first year.

Revenue

₹10L/month

Up from ₹1L a month, between December and January

AI Job Hunter

Built with Claude Code by Ashutosh Lath.

  • Claude Code
Users

1,300

Users in its first 7 days

Snowball

An AI retirement planner taken from MVP to pitch-ready in under 6 weeks, by Pratik Rajpurohit and Vardhraj Songara.

  • Replit
  • Lovable
Customers

8+

Companies sold to

Aatreus

AI-native SaaS that turns messy sales conversations into clear next steps for Indian B2B teams. Built by Dhroov Joshi.

Student showcase

From idea to AI product: what Mesa students have built

01Sales

An AI sales co-pilot

Listens to calls and surfaces real-time answers from your company documents.

02Finance

A finance approval dashboard

Streamlines fund requests with one-click approvals or clarifications.

03Operations

Automatic reimbursement emails

Extracts bill details and drafts ready-to-send reimbursement emails.

04Marketing

A generative engine optimisation dashboard

Shows brands how visible they are inside AI search results.

05Supply chain

A supply-chain optimiser

Maps customer requirements to the fewest suppliers for maximum fulfilment.

06Customer

A sentiment and review analyser

Summarises customer feedback and flags product issues.

07Operations

An order-management dashboard

Auto-organises customer orders, preferences and payments.

08Retail

A digital order-management dashboard

Auto-organises customer orders, preferences and payments in one place.

09Personal finance

An AI retirement planner

Builds personalised SIP and long-term wealth plans instantly.

10Personal finance

A credit card recommender

Picks the best card based on spending habits, rewards and eligibility.

11Content

An AI content engine

Builds your unique writing style guide and recreates posts in your tone.

12Careers

An AI job-application platform

Tailors resumes, scrapes listings and sends personalised cold emails.

13Careers

An AI interview trainer

Helps people master communication and self-presentation.

14Careers

A mock interview simulator

Analyses your LinkedIn and simulates real interviewer personas.

15Health

A fitness app

Finds people with your body type and reverse-engineers a plan for you.

16Education

An adaptive SAT prep engine

Builds a personalised maths roadmap with diagnostics and smart mock tests.

17Education

An AI essay facilitator

Helps IBDP students prepare, correct essays and track progress.

18Wellbeing

A Gita chatbot

Gives verse-backed, contextual guidance tailored to the user.

Inside the build sessions

A student presenting an AI product on stage
Students working through a build session around a table
Two students demoing their product on a screen
A student in a Mesa t-shirt building a dashboard on a laptop
A team discussing their build with a mentor
Students working on laptops in the Mesa lounge

What students and parents ask.

  • Do I need to know how to code?

    No. Term 1 starts from zero, with prompt engineering, reading API docs and no-code app deployment. Vibe coding comes in Term 3, and fine-tuning and multi-agent systems follow from Term 4.

  • Is this theory or building?

    Building. Every course ends in something that works, and every build is deployed as a live link. Concepts are taught so students can build better, not to be memorised.

  • Won't the tools be out of date in four years?

    Some will. That's why we review the stack every cohort and teach the thinking underneath it: how to break a problem down, describe it clearly, verify outputs and design systems that don't break. Those skills transfer to whatever tool comes next.

  • How much of the programme is AI?

    The AI curriculum is 150 hours across six terms, running from no-code tools to fine-tuning, and students become fluent in 25+ AI tools along the way.

  • Who judges the work?

    Practising operators and outside founders. They judge the AI Showcase each term and give the kind of feedback students would get on the job.

Find a problem. Build the workflow. Show the impact.

Six terms of AI, a product of your own, and Demo Day to pitch what you built.