#Claude interview practice
148 related articles
·7 min
LangChain.js + Nuxt.js: An AI Full-Stack Advancement Path for Frontend Engineers
Frontend hiring now treats AI capabilities as a core assessment, covering RAG knowledge bases, AI Agent development, and LangChain.js engineering. Learn how LangChain.js + Nuxt.js helps frontend developers build memory- and retrieval-capable AI full-stack apps.
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·6 min
From Frontend Engineer to AI Agent Developer: A Complete High-Paying Skill Tree Breakdown
Pure frontend roles are shrinking; AI Agent development is the high-salary divide. This guide breaks down the full skill tree for frontend engineers pivoting to AI: TypeScript, frameworks, AI productivity, and Agent core concepts (MCP, Tool Calling, Skill).
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·4 min
Building an AI Agent Framework from Scratch: Deep Dive into Tool Calling, Memory, and Dual-Model Scheduling
Build an AI Agent from scratch — no frameworks. Deep dive into Function Call schema design, MCP remote mirroring, dual-model routing, and short-term memory management.
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·4 min
Frontend to Full-Stack AI: A Complete NestJS + LangChain Roadmap
Pure frontend roles are shrinking fast. Learn how mastering NestJS and LangChain AI agent development can unlock a 20–30% salary boost on your full-stack AI transition path.
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·3 min
Claude Code in Practice: Writing Maintainable AI Code with the Harness Methodology
Learn how to write controllable, maintainable AI code using the Harness methodology with Claude Code. Covers SDD, Agent orchestration, and enterprise-grade AI programming practices.
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·3 min
Harness Architecture Explained: The Next-Generation Design Paradigm for Agent Development
A deep dive into Harness Architecture — the next-gen Agent design paradigm. Covers its evolution from prompt engineering and context engineering, multi-agent collaboration, sandbox security, feedback loops, and why it's a must-have for LLM developer interviews.
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·2 min
Marketing Skills: An Analysis of the Open-Source Project Injecting Marketing Expertise into Claude Code
Explore how the open-source project marketingskills injects CRO, SEO, and copywriting expertise into Claude Code and AI Agents, and how the Skills paradigm transforms AI into domain specialists.
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·3 min
Harness Engineering in Practice: A Guide to Enterprise-Grade Multi-Agent System Architecture
A deep dive into Harness Engineering architecture: building an AI procurement assistant on ERP systems, covering multi-agent orchestration, MCP protocol, ASGI deployment, and sandbox isolation.
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·3 min
Why Claude Code Ditched RAG for Grep: The Engineering Logic Behind the Decision
Why did Claude Code abandon RAG for Grep? Breaking down the three root causes — undiagnosability, the multiplication effect, and index staleness — behind the shift to Agentic Search.
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·7 min
AI Agent Development: A Four-Stage Competency Model from 15K to 40K RMB Salary Growth Path
A detailed four-stage competency model for AI Agent development: from Python/RAG basics (15K) to workflow orchestration (20K), inference optimization (30K), and Agent cluster governance (40K RMB).
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·2 min
Harness Engineering Architecture Explained: An Essential Skill for AI Agent Developer Roles
Harness Engineering is becoming a must-have skill for AI agent developer roles. Learn the architecture, how top agent products use it, and how to practice with LangChain DeepAgents.
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·3 min
Agent + Skill Architecture: A Practical Guide to AI-Driven End-to-End Automated Testing
Learn how to build an AI-driven API automation testing framework using Agent+Skill architecture with Claude Code, covering test case generation, script execution, and report output.
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·4 min
LangGraph.js Practical Guide: A Frontend Engineer's Path to AI Agent Development
A practical LangGraph.js guide for frontend engineers covering LangGraph vs LangChain comparison, workflow vs general-purpose agent types, and layered Agent architecture design.
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·4 min
Ali Abdaal's Complete Hands-On Guide to Building AI Tools with Claude Code
YouTuber Ali Abdaal shares 3 months of Claude Code experience, building a YouTube tracker, Slack bots, and AI tools from scratch with his AI Flywheel method.
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·2 min
AI LLM Development Career Path: Four Stages from Zero to $60K+/Year
A four-stage learning path for AI LLM application development: from Python basics and RAG architecture to Agent cluster orchestration, helping developers transition into AI roles.
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·4 min
Building a Coding Agent from Scratch: Creating a Codex-like AI Programming Tool
Deep dive into AI coding agent architecture: from interview-level cognition to building a Codex-like CLI agent tool, covering agents.md, Skills systems, context management, and more.
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·3 min
Agent Skills Architecture Explained: A New Paradigm for Modular AI Agent Development
A deep dive into Agent Skills architecture: core concepts, components, and how it works. Clarifies common misconceptions about Skills vs. MCP, and compares Skills with Multi-Agent architecture.
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·3 min
Three-Layer Workflow Optimization for Claude Code: Requirements Extraction, HTML Specs, and Embedded Verification in Practice
Anthropic engineer Arno shares a Claude Code workflow: AI-driven requirements extraction, HTML specs over Markdown, and DOM-embedded verification to boost AI-assisted coding efficiency.
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·2 min
AI Programming Learning Roadmap: A Complete Six-Stage Guide from Beginner to Expert
A systematic breakdown of the six-stage AI programming learning roadmap, from zero-code start to mastering Cursor and professional tools, methodology frameworks, advanced patterns, and project practice.
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·3 min
6 Practical Prompt Techniques to 10x the Quality of AI Responses
6 proven prompt techniques — role-playing, deep questioning, adversarial critique, failure pre-mortem, reverse engineering, and dual-version explanation — to dramatically improve AI output quality.
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