Azure, governance, and platform patterns. I'm taking notes.
Infrastructure metrics can't tell you if AI responses are helpful. Learn to instrument semantic quality, conversation degradation, and user outcomes.
Read MoreAI tools removed the speed limit on learning and creation. Then my body sent the invoice for months of borrowing against a balance that never existed.
RAG systems fail silently when retrieval breaks. Learn to monitor Azure AI Search, vector stores, and the retrieval pipeline that feeds your models.
Spec quality isn't a skill you can workshop. It's an emergent property of organizational health. Why training fails and what actually produces clarity.
Skip the Netflix-scale chaos. Learn to start chaos engineering in Azure with simple, safe experiments that actually improve your systems without breaking production.
Stop building useless dashboards. Learn to create Azure Workbooks that actually help your team make decisions and solve problems faster.
AI can accelerate your growth or replace it. The productivity discourse gives you metrics that feel good but tell you nothing about what's happening to your capability.
Stop monitoring AI infrastructure like web servers. Learn to instrument Azure OpenAI with queries that reveal token consumption, content filters, and cost attribution.
Two early signals reveal whether your governance initiative will succeed or fail. Learn to spot them before wasting eighteen months building something that was never going to work.
A satirical look at AI architecture complexity theater, followed by a practical guide to what Azure AI Landing Zones actually do—no token valves required.
The system doesn't just fail architects. It teaches them to fail. Here's how institutional capture turns truth-tellers into artifact producers.
The architect is the accountable party for migration success or failure. Not because leadership doesn't matter, but because translation is our job.
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