I combine behavioral psychology, AI architecture, and rigorous experimentation to build engagement systems at scale. I lead product strategy at Prodege and advise AI-native startups on growth.
Every feature starts with a behavioral hypothesis — why will this create a habit? — and is validated through experimentation designed to move fast without sacrificing statistical discipline. That's the rare combination: creative product intuition backed by analytical rigor.
Hook Model, variable rewards, habit loops applied to product architecture
Production multi-agent orchestration — systems, not wrappers
ICE scoring, Bayesian stats, multi-armed bandits at scale
Product strategy through lifecycle execution — both sides
Systems, engines, and products — not slide decks.
Designed and deployed a production AI agent ecosystem — 5+ specialized agents with orchestration — that transformed product and marketing operations. Automates experiment analysis, generates campaign briefs, and coordinates across teams. Not a chatbot. A production system replacing hours of manual work with minutes of intelligent automation.
Architected a personalization engine that dynamically optimized reward promotions based on behavioral segmentation — right offer, right time, right channel — across 50M+ monthly user interactions.
Advising on product-led growth strategy, onboarding architecture, and activation mechanics for an AI-native ESP that replaces traditional campaign workflows with an agentic AI team — bringing PLG discipline to an early-stage product serving Shopify businesses.
Building an AI cooking assistant with Claude API orchestration and Supabase. Applying behavioral design — habit formation, progressive engagement, variable rewards — to a consumer product from scratch. The best way to understand AI product development is to ship one yourself.
Behavioral insight → Design → Test → Scale.
Start with user psychology. What trigger initiates action? What reward sustains it? Design for genuine engagement, not dark patterns.
Validate everything. 3x test velocity with statistical rigor. ICE scoring to prioritize, Bayesian analysis to read faster.
Engagement systems that coordinate product, email, push, and in-app with event-driven architecture at scale.
Production multi-agent ecosystems that amplify human decisions. Systems, not wrappers.
Every experiment maps to P&L. Activation, retention, and LTV modeling connected to business outcomes.
Bridge product and marketing. Own strategy through lifecycle execution — both sides of the wall.
Open to advisory engagements, consulting projects, and conversations about consumer growth, behavioral design, and AI-powered product development.