380 related articles

An open-source automated news briefing system. No coding needed—just let an AI read the project docs to complete the entire deployment. Six-stage pipeline, four-channel search covering 16+ platforms, smart classification and dedup, daily auto-push to Feishu, completely free.

Can beginners really earn over 10,000 yuan in their first month with AI coding gigs? This article breaks down the four-week AI coding learning path week by week and objectively assesses the real monetization barriers.

Spring AI 1.0 is here — Java developers can now build AI apps without switching to Python. This guide covers LLM integration, RAG, intelligent customer service, and Agent patterns for enterprise deployment.

A systematic roadmap from LangChain and LangGraph to multi-agent development, covering RAG, Tool Calling, MCP, and more, helping developers break into AI app development.
Kronos Financial Foundation Model: Usi…
Kronos is the first open-source foundation model treating candlestick data as the "language of financial markets," using an autoregressive Transformer and earning 32K GitHub Stars. A deep dive into its principles, applications, and limits.

A Vue3 beginner tutorial centered on "learn just enough, apply immediately." A three-stage path covers reactivity, Composition API, Element Plus, and data visualization, culminating in an enterprise-grade AI health monitoring system with blood sugar management, RAG consultation, and doctor-patient collaboration.

Tongyi Qianwen Qwen-Image-3.0 image generation model gets a comprehensive upgrade: supporting 4,500-token ultra-long instructions, pixel-level detail rendering, 12-language knowledge understanding, and ancient painting restoration. This article analyzes its three core capabilities.

Can AI coding tools let non-developers replace programmers? This deep dive examines Vibe Coding's real limits, compares Claude Code vs. Codex, and reveals the methodology behind enterprise-grade AI-assisted software engineering.

In-depth analysis of Claude Code customization methodology: from access, knowledge injection to tooling. Master context window management, zero-overhead Hooks, and MCP & Skills plugin primitives to build a scalable AI software engineering workflow.

A deep dive into the DeepLearning.AI & Neo4j course 'Knowledge Graphs for RAG' — covering core concepts, vector retrieval synergy, and hands-on SEC filing demos.

Learn how to use Coze (扣子) with zero coding experience — from the Template Store to building custom AI workflows. A complete beginner's guide.

A comprehensive guide to AI-native application architecture: LLM inference, RAG retrieval (vector DB/knowledge graph/BM25), Agents, MCP tool calling, AI gateways, and observability — end-to-end.

Pi is a minimalist open-source Agent framework with just 4 default tools and under 1,000 tokens in its system prompt, with 70K GitHub stars. Deep dive into its 4 core advantages vs. Claude Code and Codex.

A complete guide to Claude Code Skills: what they are, how they differ from Plugins, three installation methods, how to write SKILL.md, trigger mechanisms, and top resource recommendations.

Andrew Ng and Anthropic's Claude Code course covers RAG development, data analysis, and Figma-to-frontend projects, with deep dives into context management, MCP tools, and CLAUDE.md architecture.

Deep dive into OpenClaw multi-agent AI programming workflows: context layering, CMUX parallel terminal management, work trees, and manager-perspective debiasing for scalable AI dev automation.

A Claude Code open-source config with 278 skills and 67 sub-agents helps developers ship a full MVP in 8 hours. Covers security scanning, silent failure detection, and experience migration. Free under MIT license, compatible with Cursor and Codex.

How can Java developers break into AI? This guide covers the AI application engineer career path, RAG knowledge base fundamentals, vector database retrieval, and enterprise-grade RAG challenges.
BAML: A Type-Safe Programming Language…
BAML is a domain-specific language for AI Agent development that uses a type system to solve unreliable LLM structured output and unmaintainable prompts.

Learn how to build a full WhatsApp AI Agent pipeline for online courses — from ad-driven lead capture and smart screening to automated service delivery and silent lead re-engagement.