Field notes from the stack.
Architecture comparisons, reference designs and practical guides on cloud, DevOps, security and AI engineering.
Secure Tool Calling: Security Best Practices for AI Agents
AI agents do more than generate text. They call APIs, query databases, update records, run workflows, and talk to external services. Each of those abilities is…
Read articleAgent Identity and Workload Authentication
AI agents and automated workloads now call internal APIs, query databases, open tickets, and trigger business workflows without a person at the keyboard. Each of those…
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RAG Architecture for Private Company Data
Somewhere in your company right now, an employee asks an AI assistant a question it can't answer, not because the model is weak, but because it…
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Enterprise Agentic AI Reference Architecture
Gartner projects that 40% of enterprise applications will feature task-specific AI agents by the end of 2026, up from under 5% just two years earlier, and…
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AWS Trainium and Inferentia vs Azure AI Accelerators vs Google TPU
Before comparing specs, there's one fact that changes how you should actually read this AWS Trainium vs Azure vs Google TPU comparison: none of these chips…
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Amazon Bedrock AgentCore vs Microsoft Foundry Agent Service vs Google Agent Engine
Building an AI agent prototype takes an afternoon. Running one reliably for thousands of concurrent enterprise users, with real identity, memory that persists correctly, tool access…
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Amazon Bedrock Knowledge Bases vs Azure AI Search and Foundry IQ vs Google RAG Engine
Introduction Enterprise AI is only as useful as the information it can reliably retrieve. A model that can't find the right internal document, or finds it…
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Amazon Kendra vs Azure AI Search vs Google Enterprise Search
Introduction The average enterprise employee spends 3.6 hours a day searching for information, according to McKinsey research, often typing "what is our vacation policy" into a…
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Amazon Bedrock Guardrails vs Azure AI Content Safety vs Google Model Armor
Introduction Every generative AI application needs some layer inspecting what goes in and what comes out, and Amazon Bedrock Guardrails, Azure AI Content Safety, and Google…
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Amazon Personalize vs Azure and Google Recommendation Architectures
Introduction Comparing Amazon Personalize vs Azure and Google recommendation architectures isn't really a three-way product comparison, and treating it like one is the first mistake most…
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Amazon Lex vs Microsoft Copilot Studio vs Google Conversational Agents
Introduction Choosing between Amazon Lex, Microsoft Copilot Studio, and Google Conversational Agents has gotten more complicated, not less, as all three platforms shift from simple chatbot…
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Amazon Comprehend vs Azure Language vs Google Cloud Natural Language
Introduction Choosing between Amazon Comprehend, Azure AI Language, and Google Cloud Natural Language usually comes down to three things: which cloud your data already lives in,…
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Amazon Rekognition vs Azure AI Vision vs Google Vision AI
Introduction Choosing between Amazon Rekognition, Azure AI Vision, and Google Vision AI usually comes down to one practical question: which platform already lives closest to the…
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