Will Murphy

An automated daily trend briefing covering social, technological, and economic domains. AI-researched and published each morning to surface the signals that matter.

A deep dive into the unique design, philosophies, and product management challenges of building AI-driven software.

A fully self-contained chess engine running inside a single HTML page. Play against an AI opponent. Built with vibe coding.

A platform to share, discover, and run GenAI prompts. Making prompt engineering accessible and collaborative for everyone working with large language models.

Use natural language prompts to create and deploy simple AI agents. Democratizing agent creation for non-technical builders and teams who want AI to work for them.

Social bookmarking and search reimagined. Save, organize, and discover ideas across the web with a community-driven approach to curation and knowledge sharing.

An interactive simulation sandbox where small business owners and enterprise leaders can "play out" scenarios like product launches, pricing changes, or market shifts in a generative environment. Moves beyond static dashboards into dynamic, explorable world models for business decision-making.

An adaptive interface layer for LLM outputs that morphs based on the intent of the response and the user's cognitive context. Instead of uniform chat bubbles, the UI automatically generates the right interaction pattern, a decision tree, a comparison table, a guided flow, based on what the AI is helping the user accomplish.

A research tool that goes beyond fact synthesis to specifically surface counter-arguments, anomalies, and dissenting evidence in any body of knowledge. Designed to prevent groupthink by mapping opposing viewpoints with full provenance, helping researchers move from "answers" to genuine understanding.

A tool that visualizes why an AI agent failed during complex, multi-step web tasks and allows a human to "steer" it back on track. Focuses on making agentic workflows more reliable in messy, real-world environments through human-in-the-loop debugging and probabilistic design principles.

A focus-management agent that uses live signals from browser activity and wearable sensor data (heart rate, movement patterns) to proactively suggest breaks, deep work modes, or task switching. Combines edge AI processing with augmented intelligence principles to optimize cognitive performance throughout the workday.