Why I write about Azure and AI
I started a PhD in machine learning at the University of Jyvaskyla in Finland: data mining, classification, metalearning, dimensionality reduction. Then I made a choice. I paused the PhD and spent 20 years building enterprise solutions on Microsoft's stack. I founded and led Richlode Solutions, a Microsoft CRM consulting practice, and have architected systems for organizations across multiple countries, delivering hundreds of projects.
Now those two worlds are colliding. Azure AI Foundry, Copilot Studio, Azure OpenAI, Document Intelligence: Microsoft is shipping AI capabilities faster than most architects can evaluate them. I understand both the ML fundamentals and the enterprise realities, because I have lived in both worlds.
That is what this site is. The honest assessment you will not find in Microsoft's launch blog posts.
What I bring to the table
Cloud Architecture
Azure Solutions Architect Expert. Enterprise cloud solutions designed for reliability, security, and cost, not what is shiny and new.
AI & Machine Learning
Started a PhD in ML 20 years ago, now evaluating and integrating Azure AI services into production systems. I know what is real and what is a demo.
Enterprise Delivery
Former CEO and founder of Richlode Solutions, a Microsoft CRM consulting practice. Hundreds of projects delivered; delivery teams totaling 50+ people across engagements. Programs shipped to Microsoft HQ and Microsoft Gold Partners. I know what works at scale.
The Full Stack
C#/.NET, TypeScript, React, Python, Power Platform, Dataverse. Architecture whiteboard to working code. That matters when evaluating AI tools.
Why az365.ai exists
Microsoft is betting everything on AI. Azure AI Foundry, Copilot across every product, AI Builder in Power Platform, autonomous agents. The pace is relentless. The documentation is comprehensive but sanitized. You find the "how" but rarely the "should you."
Where are the licensing gotchas? The features that demo well but break at scale? The architectural decisions that lock you in? The cost math on AI consumption that can blow past your budget in a week?
That is the gap this site fills. I write from the perspective of someone who has to make these things work in production, not sell them at Ignite. If something is not ready, I say so. If there is a cheaper way, I show you the numbers.
What I write about
- Azure AI services. AI Foundry, OpenAI, Document Intelligence, Cognitive Services. What works, what does not, what it actually costs.
- Copilot & AI agents. Microsoft 365 Copilot, Copilot Studio, autonomous agents. Real-world evaluation, not launch-day hype.
- Cloud architecture. Azure patterns for AI workloads, governance, security, cost optimization.
- AI adoption in the enterprise. How organizations actually integrate AI into existing Microsoft stacks (Power Platform, D365, M365).
- The math. Licensing, consumption costs, ROI analysis. The numbers Microsoft does not put in the brochure.
- Build vs buy vs wait. When to adopt, when to build custom, when something is just not ready yet.
Credentials
Personal Microsoft certifications. The architecture and AI-relevant set is shown below; the full list lives on Credly .
Architecture & AI
Development & Platform
MSc in System Engineering. PhD in Machine Learning (started, paused) at the University of Jyvaskyla, Finland: data mining, classification, metalearning, dimensionality reduction.
Get in touch
Building on Azure? Evaluating AI services? Trying to figure out if Copilot is worth the seat price? Always happy to talk shop.