218 related articles

Vibe Coding is the new AI-era programming paradigm. Describe what you want in plain language; let AI generate the code. Learn the 3-stage path: mindset, quality, and real projects.

In the AI programming era, Vibe Coding alone can only build toys. This article deeply analyzes the complete engineering path from Vibe Coding to SDD spec-driven development, covering Claude Code and Codex tool selection, the SuperPower plugin, and domestic LLM comparisons.

Java, Python, Go, or a niche language? This article rationally analyzes programming language selection across three dimensions — probability, difficulty, and growth potential — to help you escape language-choice anxiety.

What is Vibe Coding? Learn this new AI programming paradigm from scratch — no CS degree needed. Use Claude Code, Cursor, and more to build real projects by describing your ideas.

A complete Python learning path for beginners covering three modules: Fundamentals, Intermediate, and Hands-On Practice — including web scraping, office automation, and data analysis.

Learn how to build full-stack WeChat Mini Programs using only JavaScript. This guide covers cloud databases, cloud functions, and cloud storage with a real-world project.

A deep dive into LangChain, LangGraph, MCP, and enterprise AI Agent development: covering Streamable HTTP updates, DeepSeek R1 Function Calling limits, and Qwen3 agent capabilities.

Many CS students use AI to learn programming but later feel they didn't truly learn. This article breaks down the two AI learning traps and offers Socratic questioning, the Feynman Technique, and more to turn AI into a real learning accelerator.

Overwhelmed by ML math courses? This guide maps out linear algebra, calculus, and probability into a practical learning path — from core courses to reference books.
GitHub Daily · July 19: The Dual Advan…
GitHub Trending July 19: ktransformers tops the list with heterogeneous inference optimization, while jcode, cua, and AstrBot signal a maturing Agent ecosystem.

A college student's MLOps 100-day challenge documents the full journey from Python engineering and Git to Docker, model deployment, and monitoring. A practical roadmap for data scientists transitioning to ML engineering.

Why do AI results vary so dramatically? LangChain V1.3 reveals the answer: engineering mindset. Covers LangGraph, Deep Agent, RAG, Time Travel, and more.

Transitioning from software dev to AI/ML is hard to do alone. Discover why finding a study buddy beats picking the perfect course — and how peer accountability solves the consistency, judgment-free questioning, and foundation-building challenges.

How can frontend engineers transition into AI development? This guide covers four agent development directions: RAG, workflow agents, vertical agents, and general-purpose agents — with framework picks like LangChain.js.

What is Vibe Coding? Learn how AI coding tools like Cursor and Claude let anyone build real products using plain language — no coding background required.

A structured AI Agent learning path covering core principles, prompt engineering, tool use, multi-agent systems, and frameworks like LangChain, CrewAI, and Dify for enterprise deployment.

A complete guide to LangChain 1.3: LLM invocation, Agent tool calling, Harness architecture, LangGraph, RAG, and DeepAgent — build a clear, modern Agent development knowledge base.
Paper Reproduction as an Entry Point i…
How can applied math students efficiently enter Scientific Machine Learning (SciML)? This guide covers the value and pitfalls of paper reproduction, with a layered path from numerical PDEs to research.
The Complete AI Researcher Learning Ro…
A structured AI/ML learning roadmap covering Python, math, machine learning, deep learning, and MLOps — with timelines, milestones, and free resource recommendations.
The Complete Guide to Breaking Into Da…
A complete guide to breaking into data science: learning resources, degree vs. online courses, building a portfolio, and career prospects. Ideal for career changers and upskilling professionals.