#claude
19 articles tagged claude, from AI, AI Engineering, Spring AI. Latest: “Which Claude Certification Should You Take? All 4 Compared”.
Which Claude Certification Should You Take? All 4 Compared
Associate, Developer, Architect Foundations, and Architect Professional — exam specs, domain weights, who each is for, and how to pick the right one.
I Passed the Claude Certified Developer – Foundations Exam: Here's What Actually Helped
A personal account of passing the CCA Developer – Foundations exam on my first attempt — how I prepared, what caught me off guard, and my study plan.
Building AI Skills: GitHub Copilot Extensions, Claude Tools, and Reusable Agent Capabilities
One skill, three platforms. Building a custom capability for GitHub Copilot, Claude, and your own AI agents — with real code and a decision framework.
AI Code Review at Scale: How We Use Claude to Review Every PR Before Humans See It
Six months, 4,200 pull requests, and a GitHub Actions workflow that catches real bugs before your team reviews. The architecture, prompt, cost, and lessons.
AI Coding Tools in Enterprise: What 90 Days of Data Actually Shows
A 90-day study of AI coding tools across a 70-engineer team, measuring PR velocity, defect rates, and ROI. The biggest finding had nothing to do with speed.
I Passed the Claude Certified Associate – Foundations Exam: Here's What Actually Helped
A personal account of passing the CCA Associate – Foundations exam — study approach, what caught me off guard, and why it's worth your time.
CCA Professional Complete Study Guide: Everything You Need to Pass
A module-by-module study guide for the CCA Professional exam — all five modules, every decision table, all 12 trap patterns, and the 15-item checklist.
Claude Certified Architect – Professional: Complete Exam Prep Guide
A detailed prep guide for the CCA Professional exam — all 7 domains with weights, the master pattern behind every module, and a 4-phase study approach.
How I Passed the Claude Certified Architect – Foundations Exam: My Preparation Guide
A first-person prep guide for the CCA Foundations exam — the five domains and weights, what's on the exam, and the tips that made the difference.
Claude vs GPT for Enterprise: An Honest Comparison
A vendor-neutral comparison of Anthropic's Claude and OpenAI's GPT for enterprise use — reasoning, tool use, cost, data privacy, deployment, and how to 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 solve different problems — a clear comparison and guidance on when to use each.
Spring AI: From Beginner to Expert, Course Overview
A 7-lesson Spring AI course for Java teams: setup, prompting, tool calling, RAG, MCP, choosing a model and running AI features in production.
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.