I'm a Software Engineer and Product Management professional with an engineering background, focused on turning user and business problems into practical, scalable products.

I work across the product lifecycle — from problem discovery, user research, and product strategy to requirements, prioritization, execution, and launch.

My engineering experience allows me to work closely with technical teams and understand the realities behind product decisions, APIs, architecture, data, and implementation.

• 🔎 Understanding user problems and finding the right product opportunity
• 🧩 Turning ambiguous problems into clear product requirements
• 🗺️ Defining product strategy, roadmaps, and MVPs
• 🤝 Working across product, engineering, design, and business teams
• 🤖 Building and exploring AI-powered products
• 📊 Using data and experiments to improve product decisions
• 🚀 Taking products from idea → MVP → production → iteration

Product Strategy

• Product Discovery
• User Research
• Problem Definition
• Competitive Analysis
• Product Vision
• Product Roadmapping
• MVP Definition
• Feature Prioritization

Product Execution

• PRDs
• User Stories
• Acceptance Criteria
• Backlog Management
• Sprint Planning
• Agile / Scrum
• Release Planning
• Stakeholder Management
• Cross-functional Collaboration

Product Analytics

• Product Metrics
• KPI Definition
• Funnel Analysis
• User Behavior Analysis
• Experimentation / A/B Testing
• Product Performance Analysis

AI Product Management

• Generative AI
• AI Product Discovery
• LLM-powered Products
• AI Feature Design
• AI UX
• AI Product Evaluation
• Responsible AI

I started from the engineering side, which gives me a strong technical foundation for working with engineering teams.

Product Management • AI • UX • Full-Stack Development

A compatibility-focused roommate discovery platform designed to help users find people they can actually live with — beyond traditional filters such as location and budget.

• 🔎 User research & problem discovery
• 👥 User personas & journey mapping
• 🧩 MVP definition
• 📝 Product requirements & user stories
• 🗺️ Product roadmap
• 🎯 Feature prioritization
• 🤖 AI-assisted compatibility matching
• 📊 Product metrics & experimentation
• 🎨 UX & interaction design

Profile → Preferences → Match → Understand → Connect → Outcome

AI • Product Strategy • Generative AI • UX

An AI-powered product focused on reducing repetitive work and helping users find relevant information faster.

• Problem discovery
• User journey
• AI feature definition
• MVP planning
• Conversational UX
• AI evaluation
• Product metrics
• Human-in-the-loop design

Product Analytics • SQL • Data • Product Strategy

A product analytics system designed to help teams understand user behavior and identify opportunities for product improvement.

• Activation
• Retention
• Conversion
• Churn
• Feature adoption
• Engagement
• Revenue

Where are users dropping off?

Which features create the most value?

What should we build next?

I generally think about products through this framework:

                 USER PROBLEM
                      ↓
                USER RESEARCH
                      ↓
              PROBLEM VALIDATION
                      ↓
               PRODUCT STRATEGY
                      ↓
              MVP DEFINITION
                      ↓
              PRIORITIZATION
                      ↓
            PRD + USER STORIES
                      ↓
             DESIGN + ENGINEERING
                      ↓
                  LAUNCH
                      ↓
                MEASURE
                      ↓
                ITERATE

The goal isn't simply to build more features.

It's to build the right thing for the right problem.

Depending on the product, I focus on metrics across the complete user journey:

Don't start with a feature.

Start with understanding why the problem exists.

An MVP should validate the most important assumption, not contain every possible feature.

Every major product decision should have a reason behind it.

Metrics don't replace product judgment, but they make assumptions testable.

AI isn't a feature by itself.

The question is:

Does AI create meaningful user or business value here?

Strong products come from close collaboration between users, product, design, and engineering.

I document product decisions and thinking through:

• Product Requirement Documents
• User Personas
• User Journey Maps
• Competitive Analysis
• Product Roadmaps
• Feature Prioritization
• User Stories
• Acceptance Criteria
• Product Metrics
• Experiment Plans
• Technical Architecture
• AI Product Specifications

I'm currently exploring opportunities in:

Product Management • Technical Product Management • Product Ownership • Technical Project Management

If you're working on interesting products involving AI, SaaS, consumer technology, or 0→1 product development, I'd love to connect.