Teaching Entrepreneurially: Accounting Vibes
by Marcus Birkenkrahe
To many of my students, “entrepreneurship” just means “business as usual.” They couldn’t be more wrong.
To me, entrepreneurship is the opposite of routine. It’s about acting under uncertainty, building something that didn’t exist yesterday, and learning fast enough to keep it alive. And in the age of AI (a term I’ll now use without quotation marks) that mindset matters more than ever.
We’ve crossed a line. AI is no longer a phase, a hype cycle, or a tool for early adopters. It’s becoming the new normal. And that shift favors people who can implement over people who merely have ideas.
Ideas, after all, have always been cheap. Humans generate them endlessly — many are impractical, half-formed, or wildly unrealistic. What has always distinguished entrepreneurs isn’t the idea itself, but the speed, quality, and persistence of execution.
In that sense, the AI age doesn’t diminish entrepreneurship. It amplifies it. This shift has forced me to rethink how we teach.
Consider the defining ventures of the last decade, from SpaceX to your local disruptor. Their success wasn’t defined solely by the novelty of the idea. It was defined by relentless implementation—shipping, iterating, failing publicly, and trying again. Most of this predates the explosion of generative AI in late 2022.
I don’t claim deep credentials as an entrepreneur. I’ve mentored startups and served briefly as a business angel in Berlin, but I haven’t built a company myself. What I do know is teaching — and AI pushes teaching in a far more entrepreneurial direction than traditional pedagogy ever did, even in disciplines that seem anything but entrepreneurial.
Accounting, for example.
A recent story from my colleague Shensi Wang, Assistant Professor of Accounting at Lyon College, captures this shift perfectly. After reading about “vibe coding” - the emerging practice of writing code using natural language prompts rather than technical syntax - she didn’t just file the idea away. She registered for a course, used AI to build simple applications for budgeting and quizzes, and brought those tools directly into her Accounting Systems class. Students will now learn these skills as part of their final project.
Accounting isn’t supposed to look like this — at least not in the traditional imagination. And that’s exactly the point.
Accounting systems is fundamentally about business data analysis. Research from Stanford shows that finance and accounting are among the industries most affected by AI. In the article Shensi read, an accountant in Singapore, worried about job security, learned vibe coding and began building small apps to solve problems in his daily work. He didn’t pivot careers. He augmented his practice.
That’s entrepreneurial teaching.
Not because it’s about startups or venture capital, but because it emphasizes building, adapting, and creating value under real constraints. The instructor isn’t merely transmitting knowledge empathetically or scaffolding content step by step. Instead, they are modeling action: Here’s a tool. Here’s a problem. Let’s build something that works.
AI doesn’t make teaching more human in the sentimental sense, even if the interface is conversational. It makes it more entrepreneurial. Less about coverage, more about capability. Less about empathy as reassurance, more about confidence through execution.
And perhaps that’s the uncomfortable truth: the future of teaching isn’t softer or more traditional. It’s bolder, faster, and more experimental — even in accounting.
Especially in accounting.
PS: I used generative AI in shaping this article much as I think we’ll increasingly use it in teaching—not to replace judgment or ideas, but to support faster experimentation and execution.