Nine years at the top table of enterprise software — CXO relationships, India's biggest brands, $2M+ ARR — and not a line of code among them. AI had been a fascination since 2019, seen up close in the conversational-AI trenches at Haptik, but never something he built. Then the call to build took over. In thirty days of vibe coding and harness engineering, he shipped an autonomous AI operating system that independently arrived at architectures the research world had only just named.
Nobody builds an autonomous AI system in a month by accident. The leap only looks sudden — here's the road that made it inevitable.
The same building power, aimed at the domain he knows cold. Three harness initiatives to rebuild Customer Success from the inside — AI doing the surfacing and preparing, the human staying in the decision seat.
Built by someone who's lived every one of these problems from the customer's side of the table.
Chief Commander AI runs underneath everything he does — a self-correcting, compounding intelligence harness, built in thirty days and running in production every day since.
And the OS wasn't the only thing. Caby — an autonomous Telegram bot. A self-running video pipeline. All from the same instinct: stop hunting for projects, solve the real problem in front of you.
No papers, no playbooks. Just first-principles instinct about what a reliable AI system needs — and, again and again, the research world arrived at the same place.
The industry arrived from the platform side. He arrived from the human side. Same architecture — his just happens to work for a real person.
Four moments. Click any to see what's behind it.
Claude assessed the harness against a global benchmark of practitioners. No self-reporting. No external panel. The system was audited, scored, benchmarked — and the result surprised even Raj.
Among non-engineer Claude practitioners worldwide. This intersection — CS domain depth + AI infrastructure builder — doesn't exist in market.
First-ever run of the system-design-check agent. Caught a regression and fixed it autonomously in the same run.
The long-term vision is products. But first — join an organisation serious about making AI work at scale, and sharpen harness engineering at enterprise level. Chief Commander AI is the proof of work. This site is the portfolio.
A role where I implement AI harness engineering at enterprise level — helping teams build reliable, repeatable AI workflows that actually ship
Organisations serious about the gap between AI capability and AI reliability in production
Teams where CS domain expertise + AI infrastructure thinking = genuine competitive advantage