The Advanced Claude Code Patterns Most Users Never Reach
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I'm thrilled to announce the definitive course on Claude Code, created with @AnthropicAI and taught by Elie Schoppik @eschoppik. If you want to use highly agentic coding - where AI works autonomously for many minutes or longer, not just completing code snippets - this is it. Claude Code has been a game-changer for many developers (including me!), but there's real depth to using it well. This comprehensive course covers everything from fundamentals to advanced patterns. After this short course, you'll be able to: - Orchestrate multiple Claude subagents to work on different parts of your codebase simultaneously - Tag Claude in GitHub issues and have it autonomously create, review, and merge pull requests - Transform messy Jupyter notebooks into clean, production-ready dashboards - Use MCP tools like Playwright so Claude can see what's wrong with your UI and fix it autonomously Whether you're new to Claude Code or already using it, you'll discover powerful capabilities that can fundamentally change how you build software. I'm very excited about what agentic coding lets everyone now do. Please take this course!
Lots of buzz on Claude Code here today. This short course, created with Anthropic, is the best way to learn to use it well. Please enjoy it! https://t.co/DvEZ8NWq12
Context
The Claude Code course developed with Anthropic focuses on giving a coding assistant enough and feedback to work through a project. Its published curriculum covers identifying relevant files, recording project guidance and asking the to plan before implementing changes.
Browser access makes the feedback cycle concrete. The course describes connecting Playwright through , an interface for external tools, so the agent can open a browser, capture screenshots and use them to improve an application's interface. This connects generated code to an observable result. It is a taught development pattern, with the course description establishing its scope rather than a measured productivity gain.
- context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
- AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
- MCP — The Model Context Protocol — an open standard that lets any AI assistant plug into any tool or data source without custom integration code.
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