⚡ AI-powered feature prioritization dashboard for PMs. RICE scoring, 2x2 Effort vs Impact matrix & NOW/NEXT/LATER sprint roadmaps powered by NVIDIA NIM & Llama 3.3 70B.

Optimización de ingresos e-commerce mediante priorización ICE/RICE y análisis de Tests A/B. Implementación robusta con Mann-Whitney U, corrección de Bonferroni y filtrado técnico de outliers (P96/P97) para identificar el impacto real en conversión. Desarrollado con Python y Pandas 3.0 (PyArrow backend) para procesamiento de alto rendimiento.

RICE, PR/FAQ, JTBD, HITL, OKR templates used in real AI product builds · not theory

An open-source workspace for product teams to run RICE, ICE, MoSCoW, and Kano prioritization.

A single-file sprint prioritization tool built around the RICE framework, with live scoring, roadmap sequencing, and a full document export.

Job-ready Product Owner portfolio featuring real-world case studies, Jira agile boards, user stories, roadmaps, dashboards, stakeholder matrices, PRDs, and data-driven product artifacts.

A privacy-first prioritisation tool for product teams. RICE, Kano, and Value vs Effort frameworks. No accounts, no tracking, no data leaving your browser.

Outcome-Based Solo Dev Productivity App

RICE scoring & prioritisation checklist — a practical framework for PMs

Independent Dodo Pizza growth-strategy case: field research, unit economics, experiment design, and modeled expansion scenarios.

Systematic feature prioritization using RICE methodology with statistical A/B test validation. Built to demonstrate PM skills in prioritization, data analysis, and technical communication.

End-to-end product strategy for converting casual bike-share riders into annual members. 150K rides analyzed, K-means clustering for personas, RICE prioritization, live dashboard.

Product specification for Calendar Widget Wizard - HealthForge (healthcare low-code platform) recruitment case study. Complete PM documentation: research, RICE prioritization, solution design, PRD, user stories. Built with Product Builder methodology. 80 pages | 52 story points.

Tarazu — decision intelligence for product teams. Score with RICE, visualize tradeoffs, and capture rationale with explainable AI. Built with Next.js, Claude, Clerk, and Supabase.

Revenue optimization project for an online store. Applied ICE/RICE frameworks for hypothesis prioritization and conducted a rigorous A/B test analysis. Managed statistical significance, data filtering (outliers), and conversion rate modeling to drive data-led business decisions.

Customer reviews → a weekly, RICE-prioritized product-discovery digest for PMs. Live ingestion + RAG chat + a Sample/Live data toggle