Sangam Gowda

About

I didn't start out chasing AI because it was the hot thing to chase. I started because I've always been the kind of person who can't walk away from a problem until I actually understand why it's broken, not until it's patched, until it's understood. That's a harder standard to hold yourself to than it sounds, and it's the one thing about how I work that hasn't changed since day one. That instinct is still what drives me. Less than two years into this field, I've already had to build things nobody handed me a blueprint for: forecasting models trained against over a decade of historical data, a computer vision system wired into physical hardware, an agricultural intelligence pipeline built with no prior data to lean on. I've also gotten things wrong, misread what a stakeholder actually needed, learned the hard way that a technically correct answer isn't the same as a useful one, watched a well-built model matter less than a well-explained one. I'd rather own that than pretend the last year has been a straight line up. What I'm chasing now is depth, real fluency in agentic systems, retrieval, and multi-model orchestration, not just the vocabulary of it. I think the next wave of useful AI isn't going to live in benchmarks. It's going to live in systems that sit between messy real-world data and the humans who have to trust the decisions coming out the other side. That's the work I want to spend the next decade getting good at. I'm early in that journey, and I'm not interested in overstating where I am. But I move fast, I don't fake understanding I don't have, and I'd rather be in the room with people solving problems that don't have playbooks yet than comfortable somewhere with one. If that's you, let's talk.

Skills