✦ About Me
I don't just build products — I decode human behavior.
Most of my work begins with curiosity — tearing apart products, studying user psychology, questioning assumptions, and rebuilding ideas into smarter, faster, and more intuitive systems powered by data, strategy, and AI.
Finding invisible gaps inside broken systems, and turning complex problems into scalable AI-driven experiences people actually want to use.
9+
Years in Financial Services
20+
0→1 Products Shipped & Scaled
AI-First
Product Thinking & Execution
5
Verticals: FinTech · InsurTech · WasteTech · RenewTech · AI
✦ My story
Nine years of compounding context.
I started my career on the frontlines of banking, insurance, and investment advisory — sitting across real customers, understanding their fears around money, trust, and financial decisions. Over the years, while managing portfolios, acquiring clients, and scaling revenue, I realized the biggest problem wasn't just selling financial products — it was that most systems were never designed around how people actually think and behave.
That curiosity pushed me deeper into product thinking, user psychology, AI, and fintech innovation. I began breaking down products, studying growth loops, researching AI systems, and identifying gaps where technology could simplify complex financial decisions at scale. Today, I combine my years of business, finance, and customer-facing experience with AI-driven product strategy to build intelligent products that don't just function — but truly solve human problems.
✦ Operating principles
How I think about building.
Outcomes over output
A roadmap is only as good as the metric it moves. I scope every initiative around a measurable customer or revenue outcome before a single ticket is written.
AI is a primitive, not a feature
LLMs and agentic workflows belong inside the core loop — onboarding, underwriting, support, retention — not bolted on as a chatbot. The win is compounding automation.
Distribution beats cleverness
Nine years in the field taught me the product that wins is the one customers can find, trust, and adopt in under a minute. GTM is a product surface.
Trust is the moat in finance
In wealth, insurance, and lending, every UX decision is a trust decision. I optimize for clarity, consent, and recoverability before I optimize for conversion.
Ship the wedge, then compound
Zero-to-one is about earning the right to build v2. I prefer a sharp wedge feature shipped in 6 weeks over a platform shipped in 6 quarters.
Founders sell before they build
I validate with real money, real signatures, and real waitlists — not surveys. If five customers won't pre-commit, the problem isn't painful enough.
✦ Where I go deep
Expertise & craft.
AI Product Strategy
- Agentic workflows
- LLM-in-the-loop UX
- AI MVP scoping
- Eval & guardrails
- Model selection & cost
Financial Services
- Mutual funds & SIP
- Life & health insurance
- Wealth advisory
- CASA & retail banking
- KYC & onboarding
0→1 Product
- Customer discovery
- Problem framing
- MVP scoping
- Pricing & packaging
- Pre-sales & design partners
Growth & GTM
- Activation loops
- CRM-led retention
- Referral mechanics
- Funnel instrumentation
- Lifecycle messaging
Analytics & Research
- Mixpanel / Amplitude
- Cohort & retention analysis
- Qual interviews
- Survey design
- North-star framing
Tooling
- Linear · Notion · Figma
- Cursor · Claude · GPT
- Supabase · Vercel
- SQL & dashboards
- Lovable
✦ Industries I build for
Where deep expertise meets real impact.
FinTech
Wealth, payments, neo-banking, underwriting
InsurTech
Distribution, claims, onboarding
WasteTech
Circular economy & traceability
RenewTech
Solar, EV, energy marketplaces
AI / Agentic
Workflow automation, copilots, evals
RAG & LLM Infra
Retrieval systems, knowledge bases, embeddings
✦ Outside the deck
When I'm not shipping.
I spend most of my time reverse-engineering products the same way an investor studies businesses — obsessively curious about why users behave the way they do. I enjoy randomly picking products across AI, FinTech, SaaS, mobility, Consumer Tech, Renew-Tech, Waste-Tech, and InsurTech — tearing them down feature by feature, mapping user journeys, identifying friction points, decoding monetization loops, and uncovering hidden product gaps that most users never notice.
Whether it's analyzing onboarding psychology of B2B, B2C, and D2C customer segments, their retention mechanics, recommendation systems, AI workflows, or growth funnels, I love thinking in terms of "what KPI is broken here and what product decision fixes it."
I regularly deep-dive into research papers, product case studies, founder interviews, behavioral design patterns, and emerging AI architectures to understand how world-class products are built and scaled. Most of my ideas start from observing everyday inefficiencies, questioning existing systems, and reimagining how AI can simplify complex human decisions through better product experiences.
