#Everything Claude Code
1195 related articles
·5 min
Loop Engineering Explained: The New Programming Paradigm Where AI Prompts Itself
Loop Engineering is a paradigm shift in AI usage. Learn how to build automated loops where agents explore, execute, and verify tasks autonomously, with a hands-on e-commerce case study.
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·5 min
Opus 5 Builds a No Man's Sky-Style Exploration Game in One Day: MCP and Sub-Agent Architecture Explained
A developer used Anthropic's Opus 5 model to build a No Man's Sky-style space exploration game in one day using Blender MCP and sub-agents. Deep dive into the technical architecture and industry implications.
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·3 min
Learning AI Large Language Models: A Complete Roadmap from Beginner to Practitioner
A systematic breakdown of the AI LLM learning roadmap covering prompt engineering, AI Agent development, RAG knowledge bases, model fine-tuning, and hands-on projects for beginners.
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·5 min
Learn AI Agent Development from Scratch: A 3-Step Practical Path to Get Started Quickly
How to learn AI Agent development from scratch? This article outlines a clear 3-step path: Python crash course, LLM theory & practice, and LangChain framework project implementation.
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·4 min
Complete Guide to Pi Coding Agent: Core Usage and Extension Techniques for a Minimalist Terminal AI Coding Tool
Complete guide to Pi coding agent: design philosophy, installation, shortcuts, session management, and 7-layer customization architecture. How this 45K-star minimalist terminal tool redefines AI coding workflows.
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·3 min
What Are Agent Skills? A Complete Guide to AI Agent Skill System Architecture and Principles
A deep dive into AI Agent Skills: their core concepts, technical implementation, the four key elements (SKILL.md, references, scripts, assets), and how Skills differ from prompts.
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·3 min
What Are Agent Skills? A Detailed Guide to AI Agent Skill System Architecture and Principles
A deep dive into AI Agent Skills: understand the core concepts and technical implementation through the four key elements — SKILL.md, references, scripts, and assets — and learn how Skills differ from prompts.
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·3 min
Deep Dive into Inkling: The First Frontier Open-Source Multimodal LLM from the West
Thinking Machines releases Inkling, an open-source multimodal LLM with near-trillion MoE parameters, 1M token context, Apache 2.0 license. Deep dive into architecture, benchmarks, and pricing.
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·4 min
The New Coding Paradigm in the AI Era: Why You Should Generate More Code Instead of Reading Every Line
Explore the new code review mindset for the AI programming era: now that code is cheap, engineers should generate massive amounts of code to verify critical code rather than obsessing over reading every line.
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·4 min
Advice from the Creator of Claude Code: Automation Is an Engineer's True Moat
Claude Code creator Boris argues top engineers should embrace AI-era automation leverage. By encoding domain knowledge into infrastructure, preview environments, and lint rules, engineers multiply output—the core path to Staff Engineer.
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·4 min
The New Coding Paradigm in the AI Era: Why You Should Generate More Code Instead of Reading Every Line
Explore the new code review mindset in the AI era: now that code is cheap, engineers should generate more code to validate critical code rather than reading every line.
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·4 min
Opus 5 Real-World Testing: Cheaper Yet Stronger — Why It's Now My Default Coding Model
In-depth testing of Claude Opus 5's coding abilities vs Fable 5 and 5.6 Sol. Why Opus 5 outperforms pricier models at half the token cost, plus selection guide and distillation explained.
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·5 min
WebMCP in Practice: Building Browser AI Agent Tools & DevTools Debugging Guide
A detailed guide to Google's WebMCP standard proposal, covering imperative and declarative tool building, smart home and car configuration demos, and Chrome DevTools debugging for AI agent tools.
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·3 min
Using AI Agents to Write Research Experiment Logs: A Complete Methodology and Workflow
A detailed guide on using AI Agents to build Research Logs for scientific experiments, covering skeleton structure, daily workflows, pre-experiment thinking standards, code change tracking, and Agent-researcher division of labor.
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·3 min
A Beginner's Guide to AI Agents: Two Learning Paths for Developers and Practitioners
How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.
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·3 min
Using AI Agents to Write Research Experiment Logs: A Complete Methodology and Workflow
Learn how to use AI Agents to build a Research Log for scientific experiments, covering structure, daily workflows, pre-experiment thinking, code change tracking, and human-AI division of labor.
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·2 min
Why 'Clean Code' Author Uncle Bob No Longer Reviews AI-Generated Code Line by Line
Clean Code author Robert C. Martin no longer reviews AI-generated code line by line, shifting to test-driven verification. We explore the logic, debate, and implications.
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·4 min
A Beginner's Guide to AI Agents: Core Principles and Learning Paths Explained
Learn AI Agent core principles from scratch: understand how Agents differ from LLMs, their execution mechanisms, why rule design matters, and find the right learning path for your goals.
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·4 min
What Is the True Nature of Large Language Models? A Super Compressor Analogy to Help You Fully Understand
Large models aren't search engines — they're more like super compressors. This article explains how LLMs compress data to learn semantic patterns, and explores the phenomenon of intelligent emergence.
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·3 min
Chinese Open-Source AI Conquers Silicon Valley: The Industry Upheaval Behind a 58% Compute Share
Chinese open-source AI models surged from under 10% to 58% of U.S. AI consumption. Kimi K3, DeepSeek, and Qwen are reshaping AI cost structures as DoorDash, Airbnb, and other Silicon Valley giants adopt them at scale.
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