Helping Harvard MBAs Become Builders Through AI

"I really wish I had known about these tools when I started working on my startup a few months ago." – HBS LTV Student

Lately, I’ve been obsessed with AI as a catalyst to help founders become 10x founders – amplifying their productivity and accelerating their experiments on the product-market fit journey,

The other day, I co-taught a hands-on workshop in the Launching Technology Ventures (LTV) class at Harvard Business School with my former student John Yang-Sammataro and my colleague Professor Christina Wallace on how to use modern AI tools to catalyze prototyping. What I didn’t expect was how much our students would teach us about the changing nature of technical advantage in startups.

For context, the class—which I’ve taught for 14 years in conjunction with a team of other faculty members like Christina to over 2000 students—uses the case method to teach about the strategies and tactics of pre-product-market fit startups. We have incorporated AI heavily in recent years, including introducing a course chatbot trained on the course’s specific cases, teaching notes, and analytical exercises.

The workshop was designed to force the students to use the modern AI tools to transform a startup idea into a lean canvas and then a prototype. In effect, helping them to conceptually go from -1 to 0.

We wanted to demonstrate to the students how AI transforms the methodology that future founders use to validate ideas and achieve product-market fit. Our goal was for students to explore the “art of the possible” with AI, critically think about the trade-offs of using AI to validate a business model, and engender confidence with tools to actually build something.

We structured the exercise into two parts. First, students pressure-tested their startup concepts using an AI business model and lean canvas generator called SparkRockets. We tested a number of these no-code AI tools for startup founders and found SparkRockets to be the best.

Second, we had the students build a website landing page for their startup from scratch using ChatGPT, Visual Studio Code, and GitHub Pages. Although SparkRockets also builds a landing page, we wanted to push the students to start with a blank screen and “program” in HTML—using English as their programming language—as a baseline and then learn how to use the tools to edit their draft landing pages. Note approximately one-third of the students had some technical background (either as software engineers or data analysts familiar with SQL/Python) and two-thirds were completely non-technical. All aspire to be founders at some point in the near term and many are actively working on their startup.

Key Takeaways from the Exercise

● AI Makes Better Builders Than We Expected. The first surprise came early. The AI tools were much more powerful and accessible than we expected. The key was just getting people started. It’s remarkable how hard it is for even the smartest, most talented people to overcome inertia and simply try these tools! With a few pointers, students with zero coding experience built and deployed functional websites within hours. We expected lots of questions. However, the office hours we hosted to troubleshoot were nearly a ghost town. Everyone got through the assignment before talking with us, even those who had never touched code in their lives before.

● Effective AI use requires management and strategic skills. The students who were most effective with the tools leveraged skills more commonly associated with a liberal arts degree than a technical class—clearly articulation their value proposition and ideal customer profile, using precise language in their step-by-step prompting, and thinking creatively and strategically along the way. Importantly, they grasped how the tools might help them run the most important experiments to test out hypotheses.

● The 10x Founder is clearly emerging. Entrepreneurs who can leverage AI tools for rapid product-market fit and scaling are building a new kind of moat. By iterating faster than founders who don’t use AI, these AI-forward founders are setting themselves up to find product-market fit in the fastest most efficient way possible. The students got the memo on the value of iteration speed. Students emphasized how quickly they could make changes, test alternatives, and evolve their ideas. With the AI business model generator and a chat app, they could rapidly flesh out and test their concepts against common knowledge and best practices before more involved real customer discovery calls. Non-technical students, especially, could iterate on something tangible for customer feedback without hiring a technical resource in a way that had previously seemed impossible.

A few salient student observations that bring these points to life:

“This exercise convinced me that if you're performing ideation and not using AI tools in the process, you're handicapping yourself unnecessarily. AI dramatically improves the process every single step of the way and is an invaluable tool.”

“I knew AI tools were useful for programming but the ease of prototyping and testing quickly became very apparent. For low-tech projects this…would delay the need for hiring engineers.”

"This has just reinforced to me how easy it is to test different ideas now because the grunt work can be done really quickly through AI tools."

“I had a separate chat going where I would ask ChatGPT how to get the best results…what's the best format to ask these questions in? Or what do you need from me to produce the most accurate results to the prompt that I'm putting in? I also…asked [ChatGPT] to organize [my paragraph] into a prompt that ChatGPT would understand.”

Implication: Methodology is The New Moat

The most profound lesson from the workshop was well summed up in one student’s statement:

“The tech is not the moat!”

In an era where AI can help anyone build, the competitive advantage in many startups is becoming less and less in technical implementation. The ability to think clearly, communicate precisely, and learn rapidly from feedback becomes even more critical when everyone has access to powerful building tools. Founders should focus on:

● Clarity of vision: How you see and interpret opportunities

● Quality of nuanced customer insights: How profoundly you understand your audience

● Speed of learning and iteration: How you learn and improve

● Ability to ask the right questions: How you analyze and problem-solve

● Leadership of employees, customers, and partners: How you build and maintain relationships

As AI increasingly commodifies technical execution, competitive advantage accrues to the effective execution of softer, more traditional business skills and knowledge of how to effectively direct more accessible technical horsepower. The return of liberal arts, perhaps?

To be clear, technical skills are not obsolete, but their value is shifting. Computers and spreadsheets didn't eliminate the need for advanced math and analysis skills. However, they shifted value away from rooms of people calculating numbers to those who knew how to derive business value from newly democratized calculations. The former human calculators found themselves out of jobs, while newly empowered analysts leveraged the tools to seize new opportunities.

Founders, whether non-technical or technical, need to keep up with AI tools if they hope to stay competitive, let alone build the new “moat.”

The projects can be viewed here: HBS AI Showcase.

And in the spirit of collaboration, here is an open-source version of the exercise: LTV Prototyping with AI Workshop

We're planning an updated version of the workshop for the spring semester in 2025 so we would welcome your feedback!