Problem framing
Define the user, context, job and constraint before discussing features.
Technical Product · AI · 0→1
I turn ambiguous problems into products teams can ship—and users can trust.
Technical product leader with six years across enterprise banking, connected products and AI. I combine product judgement with hands-on engineering depth to move from discovery to reliable delivery.
5 monthsConcept to cross-platform beta
27Controlled beta registrations
74%Registered-user completion
12Structured feedback responses
3 peopleCore contributor team
Product approach
Evidence, judgement and technical fluency.
I work across the seams where product decisions become system behaviour. That means making the user problem explicit, choosing what not to build, giving engineers clear contracts and treating feedback as evidence rather than decoration.
Outcome-led scope
Prioritise the smallest release that can deliver value and produce useful evidence.
Technical clarity
Translate product intent into workflows, API behaviour, data boundaries and failure states.
Responsible learning
Measure value honestly, expose uncertainty and keep privacy and safety as release gates.
Selected work
A real product, not a hypothetical exercise.
BERT demonstrates the full arc: discovery, MVP definition, adaptive assessment and AI design, cross-platform delivery, beta evidence and a roadmap reset based on what users actually experienced.
BERT: from behavioural concept to cross-platform beta
How I balanced contextual user value, deterministic evidence, generative AI, privacy, app-store constraints and a three-person team.
Read the case study→
PRD, KPI tree and evidence-led roadmap
Supporting artefacts showing how beta findings become requirements, measurement and prioritised decisions.
Explore product work→
Looking for technical product ownership?
I’m open to Technical Product Manager and AI Product Manager opportunities in India and suitable international markets.