Rathish Rajendran had barely landed in California before he started making connections.

Jet lag, apparently, was not going to get a vote.

Within days of arriving in the United States to pursue his master’s at UC Irvine, the software engineer from Bangalore was attending an entrepreneurship event in Newport Beach, talking with founders, and finding inspiration for an AI project of his own.

On this episode of Legacy Launchers, Rathish joins Li Lin to discuss starting over in a new country, why technical knowledge still matters when AI can write code, and what he believes makes a university education valuable beyond the classroom. His ambition is straightforward: build technology that genuinely helps people. Rathish_Pause_Edited(1)

A New Country, a Little Anxiety, and an Invitation

Moving internationally sounds exciting until you have to figure out an unfamiliar place while your body insists it is a completely different time of day.

Rathish describes arriving with both enthusiasm and anxiety. He was entering a new country, adjusting to a different culture, and preparing to live more independently.

But rather than waiting until he felt completely settled, he and his friends visited an entrepreneurship resource at UCI. That visit led to an invitation to a local event.

They went, despite the jet lag.

What stayed with Rathish was the range of people building businesses. He met student founders and an entrepreneur around 60 who was enthusiastically explaining his product. Seeing that excitement across generations challenged the idea that entrepreneurship belongs to a particular age group.

He also recalls meeting a successful founder whose humility impressed him as much as his accomplishments.

The lesson was not simply that networking might produce a useful contact. It was that being around people who care deeply about what they are building can make your own ideas feel worth pursuing.

Rathish and his friends left wanting to build something themselves. Rathish_Pause_Edited(1)

Their AI Idea Started With a Familiar Problem: Where Did We Save That?

The event produced another realization: meeting people is one thing. Organizing everything you learn from them is another.

Rathish was saving information in WhatsApp. One friend was using a notes app. Another was using Google Docs.

Back at their dorm, they had to piece everything together.

The experience inspired an application designed to accept different kinds of information—voice notes, text, images, videos, and links—and organize it so users could retrieve it later through a natural-language question.

Think of it as an AI-assisted second brain for the information you fully intended to remember.

Rathish offers a simple example: you save a video containing a high-protein recipe. Months later, you remember the general idea but not the creator, title, or location of the link. Instead of searching through multiple apps, you ask the application to find the recipe.

At the time of the interview, he and his friends were working toward that concept. It was a project they wanted to build, not a finished product being presented as an established solution.

The appeal is practical: less time reconstructing where information went, and more time doing something useful with it. Rathish_Pause_Edited(1)

If AI Can Write Code, Why Learn to Code?

Rathish’s answer is that generating something and understanding it are not the same skill.

Speaking from his experience in software engineering, he argues that knowing the underlying work helps you direct AI, evaluate its output, and recognize when something needs to change.

He illustrates the point through podcasting.

A person who understands interviews, production, and audience expectations brings a different level of judgment to AI tools than someone who has never made a podcast. The tool does not erase that experience; the experience helps determine how effectively the tool gets used.

“People who know the domain knowledge well can use these tools pretty well,” he explains.

For Rathish, the same principle applies to coding. Learning the fundamentals is not pointless simply because AI can generate code. Understanding what the system is building is part of being able to guide it.

His view is optimistic, but it comes with a responsibility: keep learning how to use the tools better.

The question is not only, Can AI do this? It is also, Do I understand the work well enough to know whether it did this well? Rathish_Pause_Edited(1)

The Degree Is Only Part of the Education

When the conversation turns to graduate school, Rathish does not start with coursework.

He starts with people.

For him, university provides access to a network: professors, alumni, fellow students, founders, and professionals whose experiences can help expand his own understanding of what is possible.

He points to the interview itself. Before coming to UCI, he had not imagined finding himself on a podcast in America. Being there created an opportunity he could not have fully planned beforehand.

That is why he sees attending university as more than collecting information. Subject knowledge can be acquired through many routes, he acknowledges. His reason for being on campus includes the relationships and conversations that come with it.

He also believes alumni can be especially willing to help because they recognize something of their younger selves in students asking for guidance.

His approach to education is active: learn the material, but also meet people, ask questions, and participate in the community around the classroom. Rathish_Pause_Edited(1)

Same Ambition, Different Paths

Having experienced Bangalore and begun exploring Southern California, Rathish offers an observation about how ambition gets expressed.

He describes Bangalore as a place with talented engineers, ambitious people, and an active culture of technology events and startups.

Among the students he had encountered in the United States, however, he noticed more people openly discussing plans to build their own companies. In his experience back home, pursuing a well-paid position at an established company often featured more prominently.

He is careful to frame this as a personal observation, not a definitive comparison between countries. He also emphasizes that India has many student founders.

The distinction is not about who has talent. It is about the different directions talented people may see themselves taking.

For Rathish, exposure to new people and possibilities is helping him explore his own direction. Rathish_Pause_Edited(1)

Building a Legacy Beyond a Job Title

Asked what he wants to accomplish over the next two years, Rathish does not name a salary, a prestigious employer, or a funding target.

He wants to become better at building AI systems that benefit humanity.

He talks specifically about making systems reliable, aligned, and safe. Whether that happens through his own company or by contributing to another organization is less important to him than believing in the work.

That gives the conversation a clear through line. His interest in networking is not separate from his interest in engineering. Both are ways of developing the ability to build something useful.

He arrived in Irvine with uncertainty. He accepted an invitation. He met people who inspired him. He noticed a problem worth exploring.

No perfect roadmap. No guarantee of success. Just curiosity followed by action.

Sometimes the beginning of a meaningful project is not a breakthrough. It is showing up, paying attention, and deciding that a problem is worth solving. Rathish_Pause_Edited(1)

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Listen to the full conversation with Rathish Rajendran on Legacy Launchers, hosted by Li Lin. Connect with Rathish on LinkedIn by searching his name.

Rathish_Rajendran_Automatic_Transcript.txt. The raw transcript contains some transcription errors, including inconsistent name spellings.