Applied AI Guides, without the jargon.
The concepts technology leaders need to master, explained by a team that has shipped applied AI to production for 10 years.
Agentic AI: what it is and why it matters for the enterprise
Agentic AI (or agentive AI) explained: how autonomous agents work, real examples, and the tools and platforms enterprises use to run them safely.
6 min readRead the guide Guide · 3 articlesAI Governance: The Enterprise Guide
What is AI governance and how to run it: responsibilities, best practices, assessment, and compliance for enterprises putting AI in production.
7 min readRead the guide Guide · 2 articlesWhat is Amazon Bedrock
Amazon Bedrock is the AWS service for running foundation models, including Claude, inside your own account with US data residency. Here is how it works and where the real engineering lives.
5 min readRead the guide Guide · 2 articlesThe Claude API: building enterprise GenAI on Anthropic
The Claude API gives enterprise teams programmatic access to Anthropic's models. A practical guide to models, tool use, MCP, and production governance.
5 min readRead the guide Guide · 3 articlesData engineering: the foundation for production AI
Data engineering for AI: pipelines, data processing, and the foundations that decide whether models reach production or stall in proof of concept.
4 min readRead the guide Guide · 4 articlesEnterprise AI: from pilot to production
Enterprise AI solutions that reach production: what separates AI for enterprise from pilots, and the operating model that makes it stick.
4 min readRead the guide Guide · 3 articlesModel Context Protocol (MCP): the integration standard for enterprise AI
Model Context Protocol (MCP) is the open standard for connecting AI models to your tools and data. Here is what it is, why it matters, and how to run it in production.
4 min readRead the guideFrom reading to production.
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