Writing
Notes on building AI systems
Long-form pieces on AI engineering, computer vision, sports intelligence, and what a decade in elite sport teaches you about building software that has to work.
What Is a Digital Twin for an Athlete?
A Digital Twin is not a 3D model of a player. It is an evolving representation of how someone actually competes, built from their match history — and it is useful precisely because it keeps changing.
Digital TwinsSports AnalyticsArtificial Intelligence5 min readTeaching AI to Understand a Squash Match
Detecting a player is the easy part. Understanding a rally means recovering structure over time — and that is where most of the real engineering in sports computer vision goes.
Computer VisionSports TechnologyAI Engineering5 min readBeyond the Scoreboard: What AI Can Learn From Sports Video
The score tells you who won. Everything explaining why is in the video — and most of it has never been extracted, because until recently nobody could afford to watch it all.
Sports AnalyticsComputer VisionSports Technology4 min readBuilding AI Systems for High-Stakes Healthcare Information
When the cost of a confident wrong answer is real, generation is the least interesting part of the system. Notes on grounding, evaluation and failure design in healthcare AI.
Healthcare AIAI EngineeringAI Agents5 min readWhat Elite Sport Taught Me About Building AI Systems
Not a motivational essay. The specific habits from a decade of competitive squash that transferred to engineering — and the ones that turned out to be actively harmful.
Building AI StartupsAI EngineeringSquash5 min read
Topics
- Artificial Intelligence
- AI Engineering
- Healthcare AI
- AI Agents
- Computer Vision
- Sports Technology
- Sports Analytics
- Digital Twins
- Squash
- Building AI Startups
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Building something at the intersection of AI and the real world?
I'm glad to hear from engineers, founders, researchers, coaches and athletes — and from anyone working on AI systems that have to be right rather than merely impressive.