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In a world with so many entrepreneurial possibilities, the Levy Spark Treks take students from the classroom into the heart of businesses — its people. These treks inspire and energize Kellogg students interested in entrepreneurship by connecting them with industry experts, and through these intimate experiences, students can build meaningful relationships with business leaders. Together they can discuss and explore innovative solutions to the world’s complex business challenges.

In this installment, Anudeep Althur ’25 MBAi Program shares details about his in-person office visits to some of the leading AI and technology companies and startups in San Francisco including butternut.ai and Open AI. He also highlights key moments and lessons from the several guest speakers he connected with throughout the trip. 

 By Anudeep Athlur 

This past spring, I participated in a Levy Spark Trek that gave an unparalleled glimpse into the heart of the AI revolution. From intimate dinners with industry pioneers and investors at Accel and Menlo, to engaging discussions with cutting-edge AI startups such as Open AI, YC incubated startup founders, and Wall Street Journalists, the journey helped me better understand the intricacies of the AI landscape while also learn about building trust and community.  

The trek was led by Professor Mark Achler and Professor Troy Henikoff, whose extensive experience in entrepreneurship and venture capital inspired us through invaluable insights throughout the trek. I was part of a group of 13 students from different Full-Time MBAs including Two-Year, One-Year, MMM and MBAi Programs and students from the Executive and Evening & Weekend MBA Programs. I appreciated our group’s diversity not only in MBA Programs but also the different backgrounds and nationalities we each represent.  

Getting up close and personal 

More than eager to begin our dive into the diverse AI landscape, we kicked off our trek with a dinner at Kin Khao, where we were joined by tech industry leaders including Sara Ittelson, a partner at Accel; Greg Rudin, general manager at Menlo Ventures and Amelia Lin, founder at Honeycomb, a generative AI startup.

The intimate environment allowed me to connect with them more personally. For example, during dinner, I chatted with Greg, who offered a profound lesson in business acumen. He told me about the importance of identifying and addressing unspoken challenges. By identifying hidden problems, you can demonstrate a deeper understanding of the market, find better product-market fit and gain trust with investors and customers.

The office visits kicked off with an invigorating start at Pilot HQ, where an engaging fireside chat between CEO Waseem Daher and Professor Mark Achler captivated our group. Waseem shared insights into Pilot’s journey since its founding in 2017 detailing the innovative tech underpinning the company’s services and explaining how they have achieved an impressive 60% gross margin. Broadly, the approach involves turning unstructured data into structured data efficiently and leverages large language models (LLMs) to enhance accuracy and trust in accounting services.

The visit to OpenAI was undoubtedly one of my most anticipated highlights of the trek. We were welcomed into the forefront of AI innovation and legislative development, where we engaged with the go-to-market team Chris Brown and Nick Pyne, as well as Che Chang, general counsel.   

Kellogg MBA students visiting Open AI to learn more about generative AI as part of their experiential learning trip
Althur (middle front, beige blazer) and his peers at OpenAI.

During our visit to Garuda Ventures, we had the privilege of speaking with Rishi Taparia, co-founder and partner. He shared insights on VC, investment strategies and his approach to finding a founder-problem fit. 

Taparia explained the firm’s investment philosophy while underscoring the importance of team dynamics and deep customer empathy. He also discussed the evolving business models in AI, comparing usage-based models driven by limited resources to future value-based models that will emerge as computer power increases. 

At the Kellogg San Francisco campus, we listened to Deepa Seetharaman, a Wall Street journalist, discuss the importance of building trust and relationships in her line of work. 

Since she doesn’t come from an engineering or tech background, I was curious about her learning process in such a technical field. When asked, she highlighted how it’s not about sounding like an expert rather staying curious and actively listening. My takeaway: listen more than you talk.  

Deepa Seetharaman, a Wall Street journalist
Deepa Seetharaman, a Wall Street Journal tech reporter, connected remotely during the visit to Northwestern University San Francisco.
 

Later, we were joined by Taren Kauffner, founder of AI Impact Lab, and David Kanter, founder and executive director at MLCommons. I learned how nonprofit venture funds are leveraging generative AI for social impact and the need to balance AI's rapid advancement with safety and ethical considerations, including bias and data limitations.  

At DG717, we met with three Y-Combinator startup founders including Pritika Mehta (butternut.ai), Praful Mathur (Sarama) and Anuja Verma (Truva). Interestingly, they all acknowledged that trust in their co-founders is crucial before addressing other startup aspects, such as weighing risks, evaluating opportunity costs and considering customer acquisition costs. However, they emphasized that true value lies in execution. 

Applying newfound insights to my MBA journey and beyond 

The Levy Spark Trek gave me some timeless lessons and reinforced other business principles — many of which I'm applying in my current role at Apple as an AIML EPM intern. Here are some of my favorites:   

Trust and relationships: As Professor Mark Achler says, “Whenever you meet someone, bring a gift and offer value first!” This approach fosters genuine and meaningful relations rather than being purely transactional.  

Building products: Never compete over price. Period. Identify with razor-sharp precision, hidden jobs to be done. This will create a competitive edge and help increase trust with investors and customers.  

Trust and risk in AI: Building trust in AI systems is central to AI startups, and it develops over time. Decision explainability will be crucial when AI systems stop being treated as black boxes and when humans can better understand how decisions are made then trust in these systems will increase.  

What VCs look for: It's not just about a good product-market fit but also a founder-problem fit. They look at how committed you are and how committed the founder is to make it work.  

Innovation = Big Data + Big Models + Big Compute: AI native applications are uniquely positioned to capture market opportunities.  

Visit the program’s webpage to learn more about Levy Spark Treks.

Read next: Inside the Internship: Ethics, AI and impact