Neo Zhang is a MSx student at the Graduate School of Business. He is interested in entrepreneurship and building AI-native knowledge systems for real-world industries.

As Sundar Pichai prepares to speak at Stanford’s commencement next month, Business Insider reports that tech CEOs may now need a “boo strategy.”

That backlash should matter to Stanford not because Pichai might face boos, but because it reveals a question every entrepreneurship classroom now has to answer: are we teaching students to adapt to the future, or to interrogate and build it responsibly?

I do not think graduates who boo AI speeches are simply rejecting technology. They are reacting to a certain kind of professional advice: AI will transform every profession, the labor market will change, learn the tools, move faster, find your edge. Some of this advice is practical. Some of it is true. But from a graduation stage, it can sound less like wisdom than surrender. It asks students to prepare for a world they are not being invited to shape.

This is why the common critique that Stanford is too career-focused feels both right and incomplete. The deeper problem is not career focus itself. It is career fatalism: treating the future as something students must optimize themselves for, rather than something they can interrogate, challenge and build with responsibility.

After a year as a graduate student at the GSB, I think Stanford’s entrepreneurship ecosystem has shown me a better version of career preparation: one that teaches students not just to adapt to the future, but to test their assumptions, listen to people closer to the problem and take responsibility for what they build.

I came here with fragments of an idea. Before Stanford, I helped build digital knowledge at scale at Zhihu, one of the largest Chinese social media companies. At the GSB, I began to see a possible next chapter: building AI-native knowledge systems for real-world industries. At first, it was mostly a set of intuitions about changing knowledge work and industries still running on fragmented information.

Stanford did not hand me a company. What it gave me was a place where an idea could be tested in public before it hardened into a story I simply wanted to believe.

That is where the campus’s professional density matters. A Stanford email address can open doors, but access is not progress. A vague note still feels vague, even from Stanford. “Can I pick your brain?” rarely gives an industry expert much to work with. “Where does the workflow break?” gives them something concrete to answer.

That difference may sound tactical, but it is educational. It moves the student from self-expression to inquiry and makes the world capable of saying, “That is not how this works.”

This is the kind of entrepreneurship education Stanford offers at its best. Not the version that turns every class into a credential, every conversation into networking and every idea into a pitch. The better version connects ambition with reality. It asks: What has changed? Who feels the pain most? What would make me abandon the idea?

Those questions matter even more in an AI moment. It is easy for builders to hide behind reckless assumptions in the process, such as believing that the model will improve. That the market will adjust or workers will reskill. But trusting that everything will work itself out can become a way to avoid responsibility for the transition.

If students are anxious about AI, the answer is not to tell them to calm down and learn the tools. One thing I have learned at Stanford is that a serious entrepreneurship education does not make uncertainty disappear. It gives students better ways to investigate it, test their assumptions and build with responsibility.

That is also why Stanford’s “network” is often misunderstood. The shallow version is transactional. The deeper version is apprenticeship to reality. You talk to founders not to imitate them, but to understand where the workflow broke. You talk to engineers, clinicians, law students, researchers, operators and customers because they know where your spitch fails.

Those conversations can be uncomfortable. They make an idea rougher. They expose legacy systems, hidden incentives, procurement rules and exhausted users. But that discomfort is the point. A serious entrepreneurship education should make students harder to fool, including by their own ambition.

So yes, universities should prepare students for AI, markets, institutions and uncertainty. Stanford has helped me see that preparation can mean something richer than passive adaptation to whatever powerful people describe as assumptions.

For entrepreneurship, the distinction is especially important. A company is not a personal branding exercise. It is an intervention in other people’s lives. If Stanford is going to produce founders in the age of AI, they should know that access is not entitlement, confidence is not evidence and a good story is not a real need.

That is what Stanford is teaching me about entrepreneurship. Not that everyone should start a company, and not that every relationship should become a professional asset. Ambition becomes more responsible when it is exposed early to people who can challenge it, sharpen it and sometimes reject it.

The commencement backlash matters because it reveals a tension universities cannot avoid. Students do need to prepare for AI. But the best lesson Stanford’s entrepreneurship ecosystem can offer is not simply how to adapt to the future. It is how to ask who the future is for, what evidence supports it, who pays for the transition and what we are responsible for building.