Introduction
In today’s fast-paced tech environment, large language models (LLMs) and AI are capturing the attention of anyone eager to build smarter tools—no advanced coding required. Meet Stephen, a student at Cornell University studying industrial and labor relations, who’s on a mission to simplify AI adoption for his peers. With just a spark of curiosity and the support of Lovable, he’s turning “what ifs” into tangible prototypes aimed at helping more people get hands-on with AI.
TL;DR
- Empowering Non-Coders: Stephen is proof that minimal coding background doesn’t have to be a barrier.
- **LLMs in Action:**He’s exploring new ways for AI to streamline everything from interview prep to search engine optimization.
- **Practical Ideation:**By focusing on real-world needs—like a smooth user experience and actionable AI suggestions—Stephen keeps users at the heart of his project.
- Lovable for Rapid Prototyping: Lovable’s chat mode and version history empower Stephen to experiment freely, teaching him coding concepts along the way.
First thing first
S: Hi Stephen, thanks for joining us. Can you introduce yourself and share a bit about your background?
St: Absolutely! I’m Stephen D'Ambrosio, an undergraduate student at Cornell University, majoring in Industrial and Labor Relations (ILR). Essentially, I study how people interact with work—covering everything from labor history to workplace psychology. I grew up near Boston, I love to run and surf, and I’m passionate about leveraging technology, especially AI, to optimize everyday tasks.
S: That’s fascinating. How did you first discover Lovable?
St: My older brother went to Babson College and works in the VC space. He heard about Lovable early on and sent it my way. At first, I played around with it a little, but I wasn’t in “startup mode” yet. Later, when I realized I wanted to build something around AI, Lovable was at the top of my mind. I came back to it and found it perfect for experimenting without deep coding knowledge.
Evolving with AI
S: Can you tell us more about the project you’re working on using Lovable?
St: Right now, I’m building a sort of “AI recommendation service.” The idea is to help people—especially those who aren’t tech-savvy—figure out which AI tools or LLMs can make their work or personal projects more efficient. You answer a few questions, and it recommends relevant AI resources along with example prompts. It’s been an iterative process, but Lovable makes it easy to test new features and restore previous versions if I make a mistake.
S: That’s really exciting. Where did you get the inspiration for such a tool?
St: It came from my own struggles! As a student, I was using ChatGPT to prep for a residential advisor interview. It was incredibly helpful, but I realized it could’ve been more efficient if I leveraged the tool’s speech features—like a mock interview scenario. That got me thinking: if I’m facing these challenges, so are others. There’s so much AI out there, and not everyone knows how to harness it. So, my project aims to make AI more approachable by showing practical, immediate applications.
S: As a student at Cornell, how do you see your peers using AI today?
St: Everyone’s using AI to some extent. Often, people use it as a study assistant or to generate writing ideas. But I see two camps: some just want quick outputs—like looking up answers—while others see AI as a long-term productivity tool. I’m trying to help folks lean into AI more deeply, so they gain valuable experience that will matter in the workforce down the line.
S: That makes sense. What role does Lovable play in this learning curve?
St: Lovable is integral to my experimenting. Its chat mode lets me brainstorm right in the project, and the version history gives me the freedom to take risks. The first time I pasted a hundred lines of code from a machine learning site into Lovable and saw it run, I was honestly blown away. Even with minimal coding background, I feel empowered to try new things because I know I can revert changes or debug with the chat feature.
You can reach out to Stephen (sjd256@cornell.edu) to reach out if you'd like to learn more or get involved about Eva.
AI trends for 2025
S: From your perspective, what are one or two AI trends that excite you the most?
St: One big one is using AI as a search engine. Even though chat-based search can be hit-or-miss today, it’s already pushing people to tinker with prompts, refine their queries, and learn AI’s nuances. Another trend is voice-based interfaces—like real-time spoken interviews or coaching sessions—where AI can interact with you in a more natural way. Both are only going to improve, and it’s smart to start using them now to stay ahead.
S: Any final thoughts or tips for anyone new to AI?
St: Don’t wait until you feel “ready.” Just start using it. Whether you’re a coder or not, practice iteration—try a feature, see what breaks, learn from it, and adjust. It’s a hands-on process. And if you get stuck, communities like Lovable’s can be really supportive. You’ll build skills faster than you think.
Conclusion
Stephen’s journey underscores a simple truth: you don’t need to be an engineer to innovate with AI. By focusing on immediate, real-world use cases—like interview prep or next-level search—he’s tapping into the transformative power of LLMs. As more students and professionals follow suit, accessible platforms like Lovable make it possible for anyone to prototype, iterate, and expand their AI horizons without fuss.
Ready to test your own big ideas with AI?
Check out Lovable and see how quickly you can turn your concept into a live, interactive application. Your only limit is your imagination—no advanced coding required.
