137 related articles

A complete AI Agent learning roadmap covering agent principles, prompt engineering, RAG, multi-agent systems, and hands-on projects — from zero to real-world deployment.

A big-tech interviewer reveals: junior/mid frontend dev is being replaced by AI. This article breaks down 3 core Vibe Coding interview questions to help you master key skills for the AI-assisted coding era.

Why has AI engineering methodology evolved from prompts to context engineering and now Harness engineering? This article examines three paradigms, key bottlenecks, and the Agent = Model + Harness formula.

A Databricks expert breaks down the complete methodology for taking AI Agents from demo to production, covering the five pillars of evaluation, observability, data foundation, multi-Agent orchestration, and AI governance, with a real eight-week banking chatbot POC case.

Using a project management system as an example, this article details how to use the Dify low-code platform to achieve AI-powered integration of enterprise internal systems through interface capture and workflow orchestration.

An in-depth walkthrough of deploying Dify 1.8.0 and building applications: three-step Docker deployment, five app types compared, and Workflow vs Chatflow use cases—build enterprise AI apps with zero code.

Google lets businesses connect their Google Business Profile to Gemini, so the AI can read operating info, reviews, and business data to offer targeted marketing advice—lowering AI barriers for SMBs.

A systematic zero-basis learning path for AI Agent development, covering Python and LLM fundamentals, five core capabilities like task planning and RAG, and LangChain hands-on practice.

Floppy disks face a dual crisis of physical aging and reading device obsolescence. This article breaks down the core methods of Cambridge's Copy That Floppy guide: physical assessment, flux-level reading, and disk imaging.

A deep dive into Claude Code Agent Teams: how they differ from Subagents, contract-first design, model allocation strategies, and a real case of 16 agents building a C compiler.

Cut through the Agentic AI hype to see the real value of agentic applications. Based on Andrew Ng's course, learn why Evals and error analysis—not framework choice—separate top developers.

A systematic Claude Code learning guide built for Chinese developers, covering ten core modules including Slash Commands, Memory, MCP, and Hooks, with a three-tier path to build an AI coding workflow in 11–13 hours.

Software speed isn't just a performance metric — it's a core feature shaping user experience and trust. Learn how responsiveness drives creativity, flow, and lasting competitive advantage.

Can AI really replace programmers? This article explains Harness Engineering principles and its three evolutionary stages, revealing real pain points of enterprise AI programming.

Andrew Ng and LangChain CEO Harrison Chase present AI Agents in LangGraph, covering five core agent design patterns and LangGraph's graph-based framework for building cyclical agentic workflows.

Andrew Ng and LangChain CEO Harrison Chase's AI Agents in LangGraph course covers five agent design patterns and LangGraph's graph-based framework for building cyclical AI workflows.

DeepSeek R1 lacks Function Calling and JSON Output by default. Qwen3's programmable thinking modes make it the top open-source agent choice. Key LLM selection pitfalls and MCP protocol updates.

A deep dive into Agent Skills and its core design philosophy — progressive disclosure. Covers middleware, dynamic tools, and Metawheel implementation for building scalable AI agents.

Learn LangGraph multi-agent development covering Supervisor and Collaboration architectures, with three hands-on projects: code assistant, prompt assistant, and WebRTC digital human.

A complete guide to Python tech freelancing: platform comparisons, milestone payment strategies, legal boundaries, delivery management, and building stable client relationships for sustainable side income.