Diary of an AI Architect

Diary of an AI Architect

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How to build a strong enterprise AI moat with context engineering and data estate
Strong models on weak data make weak enterprise agentic systems. Here's how to build a 3-layer framework to catch up before the window closes.
 • Anurag Karuparti
My AI Visual Library: 74 Animated Guides From Beginner to Advanced
Learn AI the way your brain actually wants to - visually
 • Anurag Karuparti
Ep. 6 - Why Multi-Agent Systems Are Hard (And How to Build Them Right)
Five layers every enterprise-grade agentic AI system needs that don't fall apart at scale
 • Anurag Karuparti
How Microsoft is building a complete ecosystem for Enterprise AI?
Decoding Microsoft's entire AI ecosystem, strategic play and why it is an unbeatable moat that took 20 years to build
 • Anurag Karuparti
Why graph engineering will be the next essential AI skill. Difference between prompt, context, harness, loop and graph engineering.
Prompt engineering controls one model call. Graph engineering orchestrates agents, evaluators, deterministic steps, and humans toward a reliable…
 • Anurag Karuparti
How to actually measure if your AI agent is hallucinating
If you can't prove your agent is right, you don't have an AI strategy. Here's the 3-layer Eval Stack that separates production agents from expensive…
 • Anurag Karuparti
Loop engineering for the enterprise: close the loop or fall behind
Loop engineering is the difference between an agent capable of self-evolution and one that goes extinct. Here are the six architectural layers that…
 • Anurag Karuparti
How to actually secure your AI Agents for production?
Why prompt injection is the biggest threat to agentic AI, automated red teaming is the only viable defense, and what Microsoft's approach teaches us.
 • Anurag Karuparti
How to pick the right Microsoft AI agent architecture (a decision tree)
There are 10+ ways to build AI agents on Microsoft’s stack. Most teams pick wrong because they start with tools instead of requirements. Here is the…
 • Anurag Karuparti
How context engineering can affect your organization's decision quality
Why the decisions your AI agents make at scale are only as good as the context pipeline. The organizations that master it will win
 • Anurag Karuparti
5 repo files that standardize ai-assisted software engineering in a non-deterministic world
AGENTS.md, SKILL.md, copilot-instructions.md. The .md files that bring consistency to non-deterministic AI coding by filling the model context window…
 • Anurag Karuparti
How I build multi-agent systems with GitHub Copilot and Microsoft Foundry
Why enterprises keep picking the wrong tool for the wrong job, and a simple decision framework to fix it. The build layer vs run layer distinction every…
 • Anurag Karuparti
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