Anthropic

Banner Health cut an 8-hour manual chart-prep task down to minutes with Claude, then scaled that trust into a company-wide AI rollout. Here's the playbook — and how it applies to any enterprise deploying AI agents.

A deep dive into China's booming underground economy of AI API proxies — known as 'transfer stations' — that sell Claude tokens at 90% discounts while secretly harvesting user data, committing model fraud, and feeding criminal credential markets.

Everything you need to know about Anthropic's Claude Certified Architect – Foundations (CCA-F) certification: exam structure, five domains, scenario types, and how to prepare for production-scale Claude application design.

Should you build a workflow or an agent? Learn the key differences, trade-offs, and when to use each approach for reliable AI-powered applications. Includes decision framework, hybrid patterns, and real-world examples.

Learn how to build an MCP client that bridges your application logic with server capabilities. This tutorial covers the two-layer client architecture, implementing core methods, and testing the complete flow.

Resources in MCP allow your server to expose data that can be directly included in prompts, rather than requiring tool calls to access information. This creates a more efficient way to provide context to AI models like Claude.

When building MCP servers, you need a way to test your functionality without connecting to a full application. The Python MCP SDK includes a built-in browser-based inspector that lets you debug and test your server in real-time.

A comprehensive quick-reference guide for implementing prompt caching in Claude. Includes code snippets, common patterns, debugging tips, and a production checklist.

Learn how to process PDF documents with Claude for intelligent analysis beyond simple text extraction. Covers implementation, what Claude can extract from PDFs, common use cases like contract analysis and data extraction, and production best practices.

Discover how Claude's Extended Thinking feature gives the model time to work through complex problems step-by-step. Learn when to use it, how to implement it, security considerations with the signature system, and best practices for production deployments.