#LLM application developer interview
176 related articles
·3 min
Benchmarking Popular Claude Skill Libraries: A 5-Step Core Pattern for AI Agent Development
A deep-dive evaluation of Addy Osmani, Matt Pocock, and Gary Tan's skill libraries, distilling a 5-step Research→Prototype→Plan→Build→Test agent dev loop and why the best skill system is always your own.
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·4 min
Adding a 'Repair Layer' to Open-Source Models: How DeepSeek Can Outperform Claude Opus
Independent developer Ahmad Awais found that open-source LLM failures stem from Tool Calling bugs, not model capability. A deterministic repair layer + repair hints can make DeepSeek outperform Claude Opus.
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·3 min
Building a RAG Q&A Workflow with Dify: A 4-Step Guide to Enterprise Knowledge Base Chatbots
Learn RAG fundamentals and build an enterprise knowledge base chatbot with Dify in 4 steps: data prep, model config, knowledge base import, and workflow orchestration.
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·6 min
OpenAI CFO Deep Dive: IPO Stance, Compute Shortage, and Jony Ive's New Hardware Revealed
OpenAI CFO Sarah Fryer discusses the $122B fundraise, IPO timeline, Anthropic rivalry, compute shortage crisis, and the mysterious Jony Ive hardware collaboration on the All-In Podcast.
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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
LLM Job Interviews: Multi-Agent and Harness Engineering Are Now Must-Know Topics
Deep analysis of LLM job interview essentials: Multi-Agent architecture, Harness engineering, Agent Loop, sandbox isolation, and memory management with career transition tips.
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·3 min
From Frontend Developer to AI Architect: A Complete Guide to Codex Programming Agent Design
A complete guide for frontend developers advancing to AI architects, covering the three-tier competency framework, Codex-like agent design, agents.md configuration, Skills systems, and core AI architect capabilities.
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·4 min
Feishu-Style Docs + AI Knowledge Base in Practice: A Complete Guide to RAG and TipTap Editor Development
Learn how to build a Feishu-style document system with TipTap editor, integrating AI auto-completion, document continuation, and RAG knowledge base Q&A with vector databases and Embedding.
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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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·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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·4 min
Claude + Hexels MCP Hands-On: Three Multiplayer Games from a Single Prompt, Total Cost $68
Creator Adil used Claude Fable 5 and Hexels MCP to build three multiplayer games in one afternoon with zero code for just $68, attracting nearly 4,000 players.
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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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·3 min
The Complete Evolution of RAG: A Six-Generation Journey from Naive Retrieval to Multimodal
A complete guide to RAG evolution from Naive RAG through Advanced, Agentic, Graph, and Multimodal RAG — covering core techniques, pain points solved, and real-world use cases.
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·3 min
Vue3 + SpringBoot in Practice: A Full-Stack AI Travel Recommendation Assistant Explained
Build an AI travel recommendation assistant with Vue3 and Java SpringBoot. Features intelligent itinerary planning and AI chat, perfect for beginners entering full-stack + AI development.
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·3 min
Deep Dive into Claude Sonnet 4: Replicating Lovable with Just Two Prompts
Deep dive into Claude Sonnet 4: replicate Lovable with two prompts, generate McKinsey-grade reports, build 2D games, and explore the AI Agent building block economy.
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·2 min
The 4-Stage Roadmap for AI Application Development: A Career Transition Guide from Beginner to Senior Engineer
A 4-stage roadmap for AI application development: from Python and RAG basics to Agent cluster architecture, covering the core skills needed for career growth.
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·3 min
AI Agent Hands-On Learning Path: A Complete Guide from Beginner to Enterprise-Level Development
A systematic AI Agent development learning roadmap covering prompt engineering, RAG, multi-Agent collaboration, tool calling, and more—with phased learning advice and 28 hands-on project references.
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