From Building Software to Questioning How It's Understood
I started out as a software engineer, building backend systems and APIs, focused mainly on writing clean, working code. Along the way, I kept running into the same problem on almost every project: what a client says and what a developer builds are rarely the same thing. Requirements would shift, expectations would change, and weeks of work would get redone, not because anyone was careless, but because nobody had truly understood the same thing from the start.
That gap pulled me toward a deeper question, why does this happen so often, and can AI help close it? I started exploring whether Large Language Models could act as a bridge between informal human conversation and the structured information developers actually need. Today, my work sits at the intersection of software engineering and natural language processing, with a growing focus on how AI can help machines understand human intent more clearly, not just generate text, but genuinely understand what people mean.