Focus Areas
- Artificial intelligence
- Machine learning
- Application development
- Hands-on demos and visualisations
AI, explored in public
The Curiosity Stack
A personal learning journey through AI, machine learning, and application development — building real things, sharing what works, and figuring it out in the open.
How Work Happens
- Learn by building real things
- Share the process, not just the results
- Embrace experiments that fail
- Keep it simple enough to understand
Interactive Demos
Neural Net↗
Train a tiny neural network in your browser and watch weights, loss, and decision boundaries update in real time.
InteractiveConv Net↗
See how a convolutional network reads an image layer by layer, from edge detection to pattern recognition.
InteractiveRecurrent Net↗
Train an RNN on sequence data. Watch hidden state flow through time as the network learns to remember what matters.
InteractiveDispatches
MCP and Skills: The Missing Operating Layer for Agentic Engineering
A practical look at how Model Context Protocol and Agent Skills turn AI coding agents from impressive chat interfaces into dependable engineering systems.
Beyond the Vibe: Mastering the 2026 Agentic Coding Maturity Ladder
A five-stage framework defining how developers evolve from AI chat users to orchestrators of multi-agent software ecosystems.
The AI Power Couple: Balancing a Master's Degree with NVIDIA's Dynamic Certification Edge in 2026
Why 2026 is the year to run an AI Master's degree and NVIDIA certifications side-by-side — and how to do it without burning out.
Live Projects
Learning in public — one experiment at a time.