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Getting Started with AI Agent Development: Core Concepts, Architecture, and Practical Essentials
A comprehensive guide to AI Agent development covering core concepts, the Perception-Brain-Action architecture, key differences from chatbots, four essential components, and mainstream framework selection.
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.
AI Large Language Model Zero-to-Hero Systematic Tutorial: A Complete Guide from Basics to Practice
A comprehensive 748-episode AI LLM tutorial covering Transformer architecture, Prompt Engineering, RAG, Agent, fine-tuning, and enterprise projects like AI customer service and knowledge bases.
Spec Website: An Open-Source Website Specification Checklist
Spec Website is an open-source website specification checklist covering page structure, accessibility, security, SEO, privacy, and AI agent readability to help developers verify standards compliance before launch.
The Essential Difference Between Agent Skills and MCP: Process Layer vs. Capability Layer
Deep dive into the essential difference between Skill and MCP in AI Agent development. Skill handles the process layer for codifying workflows; MCP handles the capability layer for connecting external systems.
AI Large Language Model Career Transition Roadmap: A Three-Phase Learning Guide from Zero to Enterprise-Ready
A systematic three-phase AI LLM career transition roadmap: from Transformer fundamentals to RAG, Agent & LangChain development, to LoRA fine-tuning. Build enterprise-ready skills in two months.
What Is Meta-Harness? Unpacking the Battle of AI Evaluation Frameworks
Deep dive into Meta-Harness: why AI evaluation frameworks themselves need unified management. Analyzing fragmentation, reproducibility crises, and standardization needs in AI benchmarking.
Four Core Modules of AI Agent Development: An Architecture Guide from Failure to Stable Deployment
Deep dive into four core AI Agent modules: system prompts, tool calling, RAG memory, and ReAct workflow orchestration. Solve hallucinations, loops, and build reliable agents.
Spring AI Alibaba Agent in Practice: Building Enterprise-Grade AI Agents Natively in Java
Deep dive into Spring AI Alibaba Agent framework covering core architecture, tool calling, RAG integration, multi-agent collaboration, and production deployment for Java developers.
Vibe Coding in Practice: Creating Particle Effects and Retro Camera Filters with Zero Code
A hands-on Vibe Coding walkthrough using Qwen 3.7 Max and CoderWork to build gesture-controlled 3D particle systems and retro camera filters with zero code.
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.
Whats-LLM: An AI Programming E-Book Tutorial That Even Liberal Arts Students with Zero Tech Background Can Master
Whats-LLM is an installation-free AI programming e-book for complete beginners, written by an art-student-turned-programmer, covering LLM basics, Cloud Code, and Codex with built-in quizzes and notes.
Double Your Vibe Coding Efficiency: Replace Keyboard Typing with Voice Input for Requirements
Learn how to use Windows' built-in voice input (Win+H) to boost Vibe Coding efficiency. Voice input is 2-4x faster than typing — zero cost, hands-free AI programming.
Three Modes of AI Development: A Complete Guide from Chat to Agent to IDE
A systematic guide to three AI development modes: chat-based, Agent, and AI IDE. Covers model selection, cost comparison, and use cases for beginners.
UE5.8 AI MCP Plugin Hands-On Review: Can Claude Code Reliably Write Blueprints?
Hands-on review of UE5.8's AI MCP plugin across five real-world tests — door Blueprints, pickup systems, physics collisions — analyzing Claude Code's strengths, limits, and prompt tips.
AI Agent Learning Path from Zero: A Complete Guide from Principles to Practice
A systematic AI Agent learning path covering core principles, dev environment setup, memory management, multi-agent collaboration, and hands-on projects for beginners.
OpenAI's First Custom AI Chip Jalapeño…
OpenAI's First Custom AI Chip Jalapeño: A Deep Dive into Its Full-Stack AI Platform Strategy
OpenAI unveils Jalapeño, its first custom AI chip built with Broadcom, optimized for LLM inference. A deep dive into its architecture, strategy, and impact on NVIDIA and the AI chip landscape.
The Ultimate Ollama Guide: A Complete Walkthrough for Running AI Models Locally
Complete Ollama guide: install and run open-source LLMs like DeepSeek, Llama, and Qwen locally on Windows/Mac/Linux. Free, private, and beginner-friendly.
ChatGPT Futures, Class of 2026: Who Should AI Be Built For?
In OpenAI's short film "ChatGPT Futures, Class of 2026," young AI leaders share thoughts on education equity, healthcare transformation, and individual creativity—exploring how AI should bridge divides and center humanity.
AI Agent Development: A Three-Stage Learning Roadmap from Zero to One
A systematic three-stage AI Agent development roadmap: from Python basics and LLM fundamentals, through five core capabilities like planning and tool use, to hands-on RAG projects for real-world deployment.