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Platforms & Practice

Vendor stacks, protocols, certification paths, and field notes from delivery.

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All Model Architecture13 Training & Alignment8 Inference & Serving11 Agents & Orchestration10 Reasoning & Evaluation7 Safety, Security & Governance3 Platforms & Practice11
Platforms & Practice 120 min

Claude Certified Architect - Foundations: The Complete Exam Preparation Guide

A comprehensive, interactive study guide covering every domain of the Claude Certified Architect - Foundations (CCAF) exam. Master agentic architecture, tool design, Claude Code configuration, prompt engineering, and context mana…

claude certification anthropic agent-sdk ∑ ◫
Platforms & Practice 7 min

Five Doors Into Enterprise Agentic AI: Copilot Studio, Joule Studio, Azure AI Foundry, Databricks, and LangGraph

Every major enterprise vendor now sells a way to build AI agents, and they are not competing on the same axis. The real choice is not which product is best. It is how much control you are willing to trade for how much convenience.

agents enterprise langgraph copilot-studio
Platforms & Practice 9 min

From Macros to Agency: A Short History of Automating Knowledge Work

The dream of automating office work is older than the personal computer. Tracing the line from VisiCalc through RPA to LLM agents reveals a recurring lesson: the tools that record steps break, and the tools that pursue goals are …

history automation rpa agents
Platforms & Practice 22 min

LoRA Is Not Cheap Full Fine-Tuning: What Low-Rank Adaptation Actually Changes

LoRA is usually explained as a budget approximation of full fine-tuning: same destination, less memory. Two lines of evidence say that framing is wrong. LoRA learns less, forgets less, and reaches a structurally different solutio…

peft lora qlora fine-tuning ∑ ◫
Platforms & Practice 23 min

Microsoft Azure AI Foundry: The Enterprise AI Development Platform

Microsoft has renamed its AI development platform three times in three years, from Azure AI Studio to Azure AI Foundry to Microsoft Foundry. Behind the branding churn is a genuinely ambitious consolidation: 1,900+ models, a manag…

azure ai-foundry enterprise-ai model-catalog ∑ ◫
Platforms & Practice 21 min

Model Context Protocol: How One JSON-RPC Standard Collapsed the M×N Integration Problem

Before MCP, connecting five agents to twenty tools meant writing a hundred bespoke adapters. A protocol turns that multiplication into an addition, and the math is the whole story.

mcp agents protocols tool-use ∑ ◫
Platforms & Practice 10 min

Retrieval Is a Ranking Problem: Why Your RAG System Doesn't Need a Better Embedding Model

Teams tune the embedding model and the vector database, then wonder why answers are still wrong. Both are the least important parts of the stack. Retrieval is a two-stage ranking problem, and information retrieval solved the shap…

rag retrieval reranking chunking ∑ ◫
Platforms & Practice 3 min

Stop fine-tuning for facts: the silent productivity tax of mis-matched tools

Most teams reach for fine-tuning when they should reach for retrieval. The cost is not just dollars - it is months of confused engineers trying to figure out why the model started lying again.

rag retrieval fine-tuning architecture
Platforms & Practice 26 min

The Anthropic Platform Stack: An Architect's Guide to Building on Claude

Most teams still treat Anthropic as 'the Claude API.' That framing misses the platform that has grown around it: managed agents, a universal integration protocol adopted by every major AI vendor, a governance layer with 28 securi…

anthropic claude enterprise-ai mcp ∑ ◫
Platforms & Practice 7 min

The Claude Stack Goes to Work: How Anthropic's Product Ecosystem Reshapes Marketing and Creative Labour

Anthropic stopped shipping a chatbot and started shipping an ecosystem. From Artifacts to Cowork to Design, the through-line is the same: move the model out of the chat box and into the work. For marketing teams, that change is n…

anthropic claude marketing agents
Platforms & Practice 6 min

The Quiet Standard: How the Model Context Protocol Became the USB-C of AI

The most consequential AI release of late 2024 was not a model. It was a protocol. The story of how a single open standard ended the N-times-M integration nightmare is the story of every standard that ever mattered.

mcp standards interoperability agents
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