The backstory.
It started in 2003 — training a neural network to recognize faces on a Pentium, writing TCP/IP stacks on 8051 microcontrollers, building paint clones in raw DOS graphics. A computer science degree at BMS College of Engineering, then an MBA at IIM Bangalore.
At Alcatel-Lucent, I went from writing routing protocols to running technical support strategy for a 1,000-person IP division. Then co-founded a data visualization startup. When that didn't work out, I joined Microsoft as the founding PM for Azure Backup — built the vision from scratch, growth hacked it 10x in three years, landed as leader in Gartner's Magic Quadrant.
At AWS, I spent seven years across two roles — Principal PM and then Senior Manager — launching Honeycode, creating its pricing (approved by Andy Jassy), and eventually championing a GenAI product for knowledge workers that became Q-apps, with $100MM+ revenue potential. Four patents. 300+ customer interviews across 45 enterprise accounts. Then Amazon AGI — where I led the "memory pattern" processing 5 billion data items a week across 5 lines of business.
In March 2023, I wrote a memo on the disruption potential of generative AI. I argued that AI "workers" operating under human supervision was tractable in the near term, and that chat was the wrong modality — complex tasks need iterative, asynchronous architectures with built-in validation. I estimated five years. It happened in eighteen months.
In January 2026, I left to build independently. I now run end-to-end engineering and science teams built entirely on AI agents. They build the application, generate the data, train the models, run mechanical interpretation on the results, and feed everything back into the loop — recursively improving the whole system. Claude and Codex work as teammates: Claude writes specs, Codex reviews them. Codex writes code (0.3 fix rounds per ticket), Claude reviews it (catches architectural drift). The tools on this page? I built them because I needed them to run those teams.
"Using AI agents is an empirical science. I didn't design this workflow. I tried every combination, tracked the data, and this is where it converged."