HiringBae
The AI lab I'm running right now. We help companies make their products agent-native. Building AI teammates that remember context, take initiative, and carry real work forward without constant hand-holding.
I've been taking things apart since I was a kid in Chennai. Remote controls, motors, anything with a circuit board. That curiosity turned into Arduino projects at 12, a robotics competition win at 13, and eventually a career in AI and machine learning.
Today I run an AI lab helping companies make their products agent-native. Before that, I sold a clothing brand, led 10,000+ person events, published ML research at ASU, and moved across the world. The throughline has always been the same: figure out how something works, then build something better.
Started with robots at 12. Still building.
I never wanted to just write code. I wanted to understand how things worked, build something with that understanding, and then figure out how to get it in front of people.
I got into coding through Arduino when I was 12. I wanted to understand how machines worked, so I'd open things up and figure them out.
By 13, I won a regional robotics competition. But I was never just a tech kid. I organized a drawing competition at 11 that landed in the local newspaper, and at 14 I put together a marathon, found a sponsor for it, and pulled the whole thing off.
A lot of that came from my father. He's a business guy, and I picked up his tactical thinking early. I've always thought about the bigger picture. Not just building something, but how to ship it, sell it, and scale it.
In college, I organized an event that pulled in 10,000+ registrations and reached 11,000 users.
I led a 5,000-person university event with a ₹4,00,000 budget, handling marketing, ops, and finance. I also built and marketed a custom ticketing and billing platform for it. Then I started a clothing brand, sold it locally, made good money, and eventually sold the company.
Moved to the US for my master's, worked as an ML researcher at ASU, and published a research paper. Now I'm building an AI lab focused on helping companies make their products agent-native for the future.
Everything I build comes back to the same idea: AI should be durable, context-aware, and useful enough that people actually rely on it.
The AI lab I'm running right now. We help companies make their products agent-native. Building AI teammates that remember context, take initiative, and carry real work forward without constant hand-holding.
A temporal, knowledge-graph memory layer for AI agents. Most agents lose the thread after one session. BaeMemory fixes that by giving them durable, version-aware memory. More at baememory.com.
Agents that learn from what actually happened, not just what they were told. I'm building frameworks where agents adapt based on execution outcomes and user feedback.
Research from my time at ASU. Using machine learning to speed up structural physics simulations while keeping the results physically accurate.
If you're thinking about making your product agent-native, I'd like to hear about it.
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