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What AI Policies Can Learn from 30 Years of Tech Friction at Work
AI policies are repeating 30 years of workplace tech friction—here’s what history reveals about getting governance right.
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Lunavi Introduces a Two-Tier Approach to Azure Managed Services
Two-tier Azure managed services align support levels with evolving needs.
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SCCM vs. SCOM: What's the Difference in Modern Microsoft Environments?
Learn how SCCM manages configuration and patching while SCOM monitors performance and health in modern Microsoft and hybrid environments.
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AI-Ready Data Centers: What CIOs Should Know About the Hardware Behind the New AI Frontier
AI is changing the math on how much heat and what kinds of cooling servers will now need...
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From Chaos to Consistency: Engineering Reliable AI Workflows with XML
XML structured AI instructions replace unreliable prompts with validated, repeatable workflows that improve accuracy, consistency, trust across high-stakes use cases.
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Creating a Solver for LinkedIn's Tango Puzzle Game
Algorithms and logical reasoning are used to automatically interpret and solve LinkedIn’s daily puzzle by analyzing constraints and computing the correct grid solution.
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Data Center Checklist: How to Pick The Facility For What’s Next
A strategic checklist helping organizations evaluate and select data centers that ensure reliability, scalability, and future readiness.
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Celebrating Our New Microsoft Advanced Specialization
We are excited to announce our new specialization: Microsoft Migrate Enterprise Applications in Azure. This recognition reflects the depth of our expertise and the strength of our processes
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What We’ve Learned Creating AI knowledge Assistants that Actually Work
Building effective AI Knowledge Assistants requires focusing on data quality, cost efficiency, continuous testing, and user feedback to create systems that are accurate, reliable, and trusted.