#claude
11 articles tagged claude.
How I Passed the Claude Certified Architect – Foundations Exam: My Preparation Guide
A first-person prep guide for the Anthropic CCA Foundations exam — the five domains, their weights, what actually appears on the exam, study resources, and the tips that made the difference.
Claude vs GPT for Enterprise: An Honest Comparison
A practical, vendor-neutral comparison of Anthropic's Claude and OpenAI's GPT for enterprise use — reasoning, tool use, cost, data privacy, deployment, and how to actually decide.
MCP vs Function Calling: What's the Difference (and When to Use Each)
Model Context Protocol and function calling both give LLMs access to tools — but they solve different problems. A clear comparison with guidance on when to use which.
Spring AI: From Beginner to Expert — Course Overview
A complete Spring AI course for Java teams: setup, prompting, tool calling, RAG, MCP, choosing an LLM, and production architecture.
Claude Certified Architect (Foundations): Complete Exam Prep Course
A complete, hands-on prep course for the Claude Certified Architect — Foundations exam: the five domains, curriculum with code, and a four-week plan.
Tool Calling with Spring AI
A hands-on guide to Spring AI tool calling — define @Tool methods, wire them into ChatClient, and let Claude safely call your Java services.
Building an MCP Server with Spring AI
Most MCP content is Python/TypeScript. Here's how to build an MCP server in Java with Spring AI — expose your services as tools any MCP client can use.
Structured Outputs with Claude: Reliable JSON Every Time
Parsing JSON out of prose is a production liability. A practical guide to reliable, schema-conformant structured output from Claude, with Spring AI examples.
Prompt Engineering Enterprise Guide
A systematic approach to prompt engineering for production AI systems — covering system prompts, chain-of-thought, few-shot design, security, and evaluation.
Introduction to Anthropic MCP (Model Context Protocol)
A practical guide to the Model Context Protocol — what it is, how it works, and why it matters for building interoperable enterprise AI systems.
Building Enterprise AI Agents
Architecture patterns and best practices for building production-grade AI agents that scale — from orchestration to observability.