My Recent Work: Product Leadership in Action
Each project represents a unique challenge in product development—from enterprise platforms generating millions in ARR to AI-powered experiences pushing the boundaries of conversational interfaces. These case studies showcase my approach to transforming complex requirements into scalable solutions that deliver measurable business impact.
Whether architecting subscription platforms, optimizing eCommerce ecosystems, or integrating cutting-edge AI technologies, I focus on clean execution, cross-functional alignment, and data-driven results that stakeholders can trust.”
CASE STUDY
HP Enterprise Subscription Platform: Modernizing Global Commerce Architecture
We transformed HP’s subscription onboarding from a six-week manual process into a streamlined, scalable platform that reduced customer time-to-value by 67% while generating $55M in projected ARR.
“Jack brings a keen eye for uncovering and addressing critical gaps, with an impressive talent for ensuring clear alignment across the team. His careful, thoughtful approach to product requirements is unmatched, and his ability to ask the questions others often overlook strengthened the project’s direction.” – Shell Simpson, Senior Software Architect @ Hewlett Packard (HP)
HP’s subscription business presented a significant modernization opportunity. With complex global stakeholder needs and lengthy manual processes, we saw the potential to dramatically improve customer experience while building a foundation for future growth.
Rather than rushing to build, we led an intensive discovery phase that became the project’s foundation. Working directly with key stakeholders across regions, we mapped every edge case, user journey, and technical constraint. The breakthrough came when we aligned global teams around a true MVP scope that could deliver within our aggressive timeline.
We architected a headless Adobe Commerce solution designed for scalability and speed. The platform included comprehensive ERP integration, dynamic pricing systems, and regional tax handling to support HP’s international markets. By establishing clear product requirements and fostering cross-functional alignment, we transformed what could have been a chaotic global rollout into a coordinated launch across multiple markets. The discipline to thoroughly understand the problem before building the solution became the foundation of our success.
Strategic Impact
Customer onboarding time reduced from 6 weeks to 2 weeks, while customer acquisition costs fell by 25% through streamlined processes and improved user experience.
Technical Excellence
Headless Adobe Commerce architecture enabled global scalability while reducing sales-assisted implementations by 65% through intelligent automation.
Team Leadership
Cross-functional alignment across multiple global markets and stakeholder groups, transforming complex requirements into executable roadmap under aggressive timelines.
CASE STUDY
FedEx ShopRunner Integration: Building Revenue-Generating Partner Ecosystems
We turned a stalled front-end demo into a fully functional Shopify app that generated $1M in first-year subscription revenue while establishing FedEx’s presence in the competitive eCommerce logistics market.
“He was able to gracefully maneuver and deliver in challenging circumstances… He had this great instinct to signal risks and would raise issues in a timely manner to ensure delivery commitments are on track.” – Satish Prabhakar, Director of Products, Retailer Experience & Platforms @ FedEx DataWorks)
When we arrived, the FedEx ShopRunner Connector was supposed to be ready for certification, but we discovered it was merely a front-end demo. With the previous team transitioned and minimal institutional knowledge available, we faced the challenge of building a complete integration from scratch while Shopify simultaneously launched major platform changes that required us to refactor mid-development.
Rather than treating these obstacles as setbacks, we saw them as opportunities to build something better. We rapidly assembled a hybrid team of internal and external developers, established direct partnerships with Shopify’s development team, and pivoted our architecture to leverage Shopify’s new Hydrogen framework and checkout extensibility features.
The breakthrough came when we aligned our rapid response capability with Shopify’s platform evolution. By staying agile and maintaining close collaboration across all stakeholders, we transformed what could have been a six-month delay into a competitive advantage, launching a more robust solution that positioned FedEx to capture new revenue in the evolving eCommerce landscape.
Strategic Impact
Revenue Impact $1M first-year subscription revenue from Shopify app launch, establishing new revenue channel and expanding FedEx’s eCommerce partnership ecosystem.
Technical Excellence
Successfully navigated Shopify Hydrogen migration and checkout extensibility launch during development, turning platform changes into competitive advantages through rapid refactoring.
Team Leadership
Partnership Strategy 6-month launch timeline achieved through strategic alignment with Shopify development team and hybrid internal/external development approach under constantly evolving requirements.
CASE STUDY
Speakloom AI Coach: Contextual Language Learning Through Conversational AI
I built an AI-powered language coaching platform that creates safe practice environments for contextually relevant communication skills, recognizing that speaking to a CEO requires different language constructs than speaking to a barista or on a date.
“Jack has a rare talent for simplifying complexity. He can take intricate concepts and break them down into clear, actionable insights that make everything seem manageable and straightforward.” – Alex Warns, CFO
Traditional language learning focuses on grammar and vocabulary but fails to teach the nuanced communication patterns needed for real-world scenarios. We saw an opportunity to bridge the human-AI interaction gap by combining LLMs with text-to-speech technology to create responsive, adaptive coaching that provides instantaneous feedback in low-threat environments.
The technical challenge centered on ensuring suggestions remained contextually relevant across a large number of scenario variables. We developed an adaptive prompt tuning system that could maintain persona consistency while responding to emotional cues and language constructs in real-time. Through extensive user testing across different demographics and scenarios, we fine-tuned both the language patterns and scenario frameworks.
The breakthrough came when we realized that effective AI coaching requires more than language accuracy. It needs authentic interaction patterns that mirror real-world communication dynamics. This insight shaped our approach to building conversational AI that truly understands context, not just content.
Technical Innovation
Adaptive prompt tuning system ensuring contextually relevant suggestions across multiple scenario variables, with real-time emotional awareness and persona consistency.
User Experience Design
Safe practice environments with instantaneous feedback, allowing users to develop communication skills without real-world social pressure or consequences.
AI Learning Insights
Cross-demographic testing and scenario refinement revealed new approaches to human-AI interaction design, advancing understanding of conversational AI effectiveness.
CASE STUDY
Scryblet AI Writing Assistant: Solving Context Memory in Long-Form Content Creation
I designed a RAG-powered writing assistant that maintains story timeline and context consistency across long-form content, overcoming the fundamental limitation of LLM context windows that fragment narrative continuity in extended writing projects.
“He did an excellent job prioritizing requirements, determining what was absolutely necessary for MVP and what could wait for future releases.” – Nancy Knistern, Product Owner @ Time4Learning
The challenge emerged from my personal frustration with commercial AI chat systems that lose context and consistency when writing anything beyond short-form content. Traditional LLM interactions treat each prompt as isolated, creating disconnected fragments rather than cohesive narratives that understand character development, plot progression, and thematic consistency across chapters or projects.
My solution centers on a hierarchical file system that organizes content across projects, series, books, and chapters, allowing the AI to understand structural relationships and maintain narrative coherence. I implemented a vector database architecture that enables the system to retrieve relevant context dynamically, ensuring that character details mentioned in chapter one remain consistent in chapter fifteen.
The technical breakthrough involved designing a RAG system that could work seamlessly across multiple LLM providers including Claude, OpenAI, Grok, and potentially Gemini. This multi-model approach ensures writers aren’t locked into a single AI provider while maintaining consistent memory and context retrieval regardless of the underlying language model.
Technical Architecture
Vector database integration with hierarchical file organization enabling dynamic context retrieval across projects, series, books, and chapters for consistent narrative memory.
Multi-Model Flexibility
Provider-agnostic design supporting Claude, OpenAI, Grok, and Gemini APIs, ensuring writers can leverage different AI strengths without losing project continuity.
AI Learning Insights
Personal exploration of RAG systems and AI memory, advancing understanding of context management challenges in creative AI applications and long-form content generation.