A product-driven development philosophy that replaces speculative code with deep user empathy. We map, score, and eliminate friction points before designing architectures.
Identify structural user friction, legacy platform limitations, and economic inefficiencies.
Formula: "I want to [action] while avoiding [friction] so that [business value]."
Trigger → Action → Automated System Response → Instant Resolution.
Map state machines, database relations, and API contracts directly against the user flow.
A product-driven engineering framework and agentic skill that captures real-world user friction via standardized Mad Libs formulas and autonomously translates them into secure, verified production pull requests.
A product strategy and Critical User Journey (CUJ) addressing the single-earner bias in spend-based airline loyalty programs, creating equitable status and recognition for dual-earner, co-managing households.
A Critical User Journey (CUJ) case study on replacing bloated, gamified EdTech mobile apps with an autonomous AI agent that ingests raw school feeds, triages urgent alerts from routine noise, and delivers high-signal family briefings.
A Critical User Journey (CUJ) and system architecture for multi-caregiver households to assign, swap, and synchronize school and activity pickups/drop-offs across shared Google Calendars without recurrence corruption or manual calendar chaos.
How we built a serverless, zero-cloud-cost in-browser RAG retrieval engine and Model Context Protocol (MCP) server indexing 50+ essays, podcasts, and software architectures directly inside dh.sh.
A Critical User Journey (CUJ) case study exploring how multimodal AI models (Google Gemini video), modern web game architecture, and rapid prototyping collapse the gap between a child's imagination and a production-grade interactive game in a single afternoon.
A Critical User Journey (CUJ) case study exploring how precision print calibration, active discovery quizzes, black-and-white vector line art, and speech synthesis turn stressful last-minute school culture poster assignments into an autonomous, kid-driven learning adventure.
Why LinkedIn and X starve autonomous AI agents of real human context—and how we built a recurring voice-dictation AI Interviewer and two-way Model Context Protocol (MCP) front door so agents can truly get to know humans.
An air-gapped, asynchronous post-meeting intelligence engine on Apple Silicon with persistent speaker voiceprints, acoustic sentiment analysis, and zero cloud token costs.
An automation tool and dashboard designed to bridge the gap between my global Plex Watchlist, local server libraries, and real-time TV guide schedules.
How we transformed herrington.ai into a first-class programmatic tool server for external AI agents (Muse, Instinct, Cursor, Claude Code) using a public stateless Streamable HTTP MCP architecture.
How we used CUJ-Driven Development (CDD) to eliminate cross-agent amnesia across Grok Bot, Instinct (OpenClaw), Muse, Claude Code, and Antigravity—combining a local SQLite WAL + Markdown memory plane, offline store-and-forward queuing, and a System-One decision model (Jev) Knowledge Graph.
