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ENGR 245

The Lean Launchpad - DeepTech & EdTech

Application and Interview Tips Here!

Please sign up here if you want to keep up to date in the application process for the Spring 24 class! We will frequently send out updates there including sign ups for office hours with the teaching team prior to the application deadline. 

Applications are due at midnight on February 25, 2024. They can be submitted HERE. Please only submit one application per team.

If you are looking for teammates, look at / add a slide here. You can also use the Team Formation Hub to look for potential teammates.

Info Session / Mixer / Pitch Night Schedule:

  • Monday, January 22, 2024 | 7-8pm | General Info Session + Mixer | Slides
  • Thursday, February 1, 2024 | 7-8pm | Info Session + Alumni Talk | Slides
  • Thursday, February 8, 2024 | 7-8pm | ZOOM Virtual Info Session
  • Monday, February 12, 2024 | 7-8pm | EdTech Info Session + Fireside Chat | Location: Y2E2 Room 111 | Slides
  • Thursday, February 15, 2024 | 6:30-8:30 pm | Pitch Night + Team Formation Mixer | Location: GSB room G101 | RSVP
  • Thursday, February 22, 2024 | 6:30-8:30 pm | Pitch Night + Team Formation Mixer | Location: GSB room M104 | RSVP
  • Sunday, February 25, 2024 | 11:59 pm | Application Deadline | Application Link
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What is Lean Launchpad?

Welcome to the Stanford ENGR 245 Lean Launchpad! This course provides a real-world, hands-on learning experience on what it’s like to actually start a company. This class is not about how to write a business plan. It’s not an exercise on how smart you are in a classroom or how well you use the research library to size markets. And the end result is not a PowerPoint slide deck for a VC presentation or a Y Combinator Demo Day. And it is most definitely not an incubator where you come to build the “hot-idea” that you have in mind. Instead, we are a class like no other than will teach you how to rigorously evaluate a business idea, apply the Lean Startup Methodology and maximize your chances of establishing product-market fit

This class combines theory with a ton of hands-on practice. Our goal, within the constraints of a classroom and a limited amount of time, is to give you a framework to test the business model of a startup while creating all of the pressures and demands of the real world in an early-stage startup. The class is designed to give you the experience of how to work as a team and turn an idea into a company.

What and how will you learn?

You will be getting your hands dirty talking to real customers, partners and competitors as you encounter the chaos and uncertainty of real startup life. You’ll practice evidence-based entrepreneurship, learning to use your business model to brainstorm and stress test your assumptions and determine if anyone other than you would want to buy your product. Finally, based on the customer and market feedback you gathered, you will use agile development methodologies to rapidly iterate your product or concept and build/design something customers would actually buy and use. Each week will be a new adventure in and outside the classroom as you test each part of your business idea and then share your hard-earned knowledge with the rest of the class.

  • We teach Lean Startup Theory with hands-on practice
  • You will learn how to leverage Speed, Evidence-Based Entrepreneurship, Customer Development, “Good-Enough” Decision Making, Prototyping, and much more
  • You will do so by talking to 10-15 customers per week and presenting your results every week to your classmates, mentors, and professors
  • You will have a dedicated team of world-class faculty, mentors, TAs, and classmates from across Stanford by your side to help you maximize your learning experience
ENGR 245: The Lean Launchpad

Class Introduction - Steve Blank

Due Sunday, February 25, 2024

Spring 2024 Lean Launchpad Application

Some Alumni Companies...

Blue River Technologies

Acquired by John Deere for $300M

LLP with 2 MechE MS, 3 MBAs (AgTech)



$100M raised in multiple rounds, acquired by Symphony AI

LLP with ICME PhD & Math PhD (AI-based enterprise software)



$30M raised in Series A


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