Professional story

I'm a product manager based in Bengaluru, Karnataka. My work has centred on understanding real user problems — the kind that sit below the surface of feature requests — and helping teams move toward solutions with focus and good judgment.

I'm drawn to the part of the job where ambiguity turns into clarity: writing a sharp PRD, aligning stakeholders on what matters this quarter, or finding the simpler version of a feature that still solves the problem. I care a lot about communication as a product discipline — the kind that makes execution tighter, not just meetings longer.

More recently, I've been building a working relationship with AI tools — not as novelties, but as genuine leverage points. This site is one output of that. It was scoped, planned, designed, and built with AI assistance at every layer, with my judgment making the decisions.

I'm currently exploring AI-forward product roles where the challenge is less about adopting AI and more about using it well.

Philosophy

How I think about building products

  • Start with the problem, not the feature. The most expensive mistake in product is building the wrong thing with confidence. I spend time before the roadmap, not just on it.
  • Prioritization is about tradeoffs, not rankings. A good priority decision makes explicit what you are not doing and why. Anything else is a list, not a strategy.
  • Execution quality starts with communication quality. Ambiguous specs produce ambiguous outcomes. I write for the engineer who will implement at 11pm, not the PM who will present at 9am.
  • AI is a tool with real leverage — if you use it with judgment. I use AI to think faster, draft better, and catch blind spots. I don't use it to replace the hard thinking.
  • Ship in layers, not in one heroic release. A working smaller thing beats a beautiful thing that hasn't shipped. Version one earns the right to version two.

Expertise

Where I do my best work

Product Strategy Vision, roadmaps, scope definition, and outcome framing
User Research Problem discovery, user interviews, and insight synthesis
Cross-functional Execution Aligning engineering, design, and business stakeholders
Requirements Writing PRDs, acceptance criteria, and Gherkin-style specifications
AI Workflow Design Practical AI integration in product and team workflows
Prioritization Frameworks MoSCoW, RICE, opportunity scoring, and backlog grooming