Anthropic

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.

Claude operates blindly without environment inspection. Learn why observation is essential for effective agents and how to build inspection capabilities into your tools. Includes practical patterns and real-world examples.

Stop letting users reinvent the wheel. Learn how to create battle-tested prompts in MCP servers that deliver consistent, high-quality results every time. Complete guide covering server-side implementation, client integration, and best practices.

Speed up AI responses by up to 85% and cut costs dramatically — all by letting Claude remember what it just processed. A comprehensive guide to implementing prompt caching with TypeScript and Python.

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.

The Anthropic API offers two powerful features that work exceptionally well together: the Files API and Code Execution. Learn how combining them opens up interesting possibilities for delegating complex tasks to Claude.

Model Context Protocol (MCP) is a communication layer that provides Claude with context and tools without requiring you to write tedious integration code. Learn how MCP shifts the burden of tool definitions and execution to specialized servers, saving developers thousands of lines of code.

Stop fighting with massive prompts that Claude can't handle consistently. Learn how workflow chaining produces better results by breaking complex tasks into focused, sequential steps. Includes real-world examples and best practices.

Learn how to use Claude's vision capabilities for image analysis, from basic implementation to production-ready systems. Covers technical constraints, prompting techniques that dramatically improve accuracy, and real-world examples like automated fire risk assessment.

Learn how to build an MCP server using the official Python SDK. This practical guide shows you how decorators and type hints simplify tool creation, replacing complex JSON schemas with clean, readable code.