How I Build Products

My guiding principles, process, and toolkit for building thoughtful, data-driven products.

Thoughtful design.

Structured execution.

Measurable impact.

🎨

Design Principles

Building intuitive, delightful experiences

Progressive disclosure

Show complexity only when users need it

Instant feedback

Every action gets an immediate response

Design for adoption

Great UX drives long-term retention

Hide the complexity

Simple interfaces, powerful capabilities

🚀

Product Principles

Shipping value, measuring impact

Ship incrementally

Small releases, fast feedback, continuous iteration

Measure what matters

Track adoption, speed, quality, and reliability

Define done clearly

Flags, metrics, alerts, rollback plans, and documentation

Let data decide

Metrics drive decisions, not opinions

⚙️

Execution Principles

Shipping reliably at scale

Roll out gradually

Test with small groups, measure impact, then expand

Document decisions

Written specs create clarity and alignment

AI needs structure

Ground models in reliable data, not guesses

Balance competing needs

Consider users, business, technical constraints, and stakeholders

🤖

AI & Data Principles

Building intelligent, transparent systems

Start with structure

Ground intelligence in reliable data models before applying AI

Make it explainable

Every output should be traceable to its logic or evidence, not a black box

Keep humans in the loop

AI should augment decision-making, not replace accountability or expertise

Design for trust

Clarity, privacy, and transparency are the foundations of responsible AI

My Process

Discover

▾

Identify real friction through data and user signals.

Amplitude · Jira · SQL · Confluence

Build

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Prototype fast, validate early.

Framer · Figma · Cursor · GitHub

Refine

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Measure, learn, and iterate with purpose.

Python · R · Jenkins · FastAPI