When I started working on the LLM chatbot, I knew it would be a challenge, but I didn’t expect just how much I would learn. Using GPT-3.5-turbo and Gemini-1.5-pro, I built a system capable of processing 10,000+ customer records on Google Cloud Platform (GCP) and PostgreSQL. Optimizing data flow and ensuring real-time responses pushed me to refine my approach to scalability and efficiency. But the real reward came when we saw a 96% drop in customer support response time—a clear sign that our chatbot was making a difference.

Beyond the technical side, this project also taught me the value of leadership and collaboration. I led a team of three in designing an intuitive frontend UI/UX using Node.js, JavaScript, and Python, making AI interactions seamless. Setting up a CI/CD pipeline with GCP Cloud Run, Docker, and GitHub reinforced the importance of automation in modern development. And perhaps the most fulfilling part? Mentoring an intern in Git, Agile, and software development—helping someone grow while growing myself. Looking back, this experience wasn’t just about building a chatbot; it was about building skills, relationships, and confidence in tackling complex problems.