In a world where data breaches make headlines daily and quantum computers threaten to break today’s encryption, organizations face a critical challenge: How do you enable secure collaboration across different companies, governments, and partners without compromising security or creating operational nightmares?

Current solutions force you to choose between security and collaboration. NORC (NavaTron Open Real-time Communication) is the first protocol designed specifically to solve this problem.

What is NORC?

NORC is a secure communication protocol built for organizations that need both ironclad security and practical federation. Think of it as the next evolution beyond Signal (secure but centralized) and Matrix (federated but complex) - combining the best of both worlds while preparing for the post-quantum future.

Why I Updated My Azure Maps Authentication Guide

A few years ago, I wrote a blog post about Azure Maps Authentication to help developers get started with securing their applications. At the time, the goal was simple: show how to connect to Azure Maps and choose an authentication method that fit your project. Since then, Azure has evolved, authentication standards have matured, and some of the old approaches are now considered outdated.

I’ve been watching Model Context Protocol (MCP) servers pop up everywhere as the glue between AI agents and the real world. The pitch is simple: expose tools and data through a standard protocol and suddenly your AI agents can plan trips, analyze documents, query databases, or in my case, work with maps. MCP clicked for me because it’s opinionated where it matters and unopinionated where it shouldn’t. It standardizes how clients and servers talk, but it doesn’t box you into a single stack. Think of it as the USB-C of AI integrations: one cable, many devices.  

A personal history in a few very nerdy chapters

Pac-Man

The first “computer” that really knocked on my brain wasn’t even called a computer. It was an Atari 2600 with those giant wood-paneled vibes, a plastic spaceship parked under a living-room TV. Somewhere far from home (friends of my parents), the kind of visit where adults drink coffee forever, I met Pac-Man and the notorious E.T. They weren’t just games, they were a portal. The graphics were blocky miracles, the sound was pure electricity, and my head did that little swivel where a new obsession clicks into place. I didn’t own one. I barely got to touch it. But the idea got in. That was enough.

Why I Built an AI Assistant for My Blog

I wanted my blog to do more than list posts. I wanted visitors to be able to ask natural questions about me, my work, and anything I’ve written, and get answers that cite the right articles without me hand. In my previous post I laid the infrastructure groundwork by running n8n on Azure as an orchestration layer. This article goes deeper into how I assembled the chat assistant itself and wired it to semantic search so it actually “knows” my content rather than doing a brittle keyword lookup.

Last week I joined Geospatial FM, the podcast hosted by Wilfred Waters, to talk about AI agents and the Azure Maps MCP server I had created and bloged about.

We touched on how Bing Maps is the familiar public-facing mapping service, while Azure Maps is the developer platform for bringing mapping, routing, traffic, and spatial analytics into enterprise and IoT apps. The heart of our conversation was about Model Context Protocol (MCP) and why it matters. MCP lets AI agents use tools and pull fresh data from APIs, so instead of guessing about roads, traffic, or places, an agent can call Azure Maps in real time.