16 related articles

Deep dive into the AI coding paradigm shift: from hand-crafted prompts to self-prompting agent loops. Learn how agent self-review and proactive context fetching enable scalable, high-quality AI coding.

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.

Learn how to use OpenAI Codex to build a complete cold chain logistics optimization research project from scratch, including simulated annealing implementation, experiments, figures, and LaTeX paper compilation.

Deep dive into HiClaw, an open-source multi-Agent OS built on the Matrix protocol for transparent, controllable human-AI task coordination with Human-in-the-Loop design.

An in-depth look at PySpur, the open-source visual AI Agent workflow platform, covering its core features, technical positioning, use cases, and comparisons with LangFlow and Dify.

A junior student uses Cursor and Vibe Coding to build a multi-agent system with 51 AI officials modeled on China's Three Departments and Six Ministries, featuring task distribution, approval workflows, and Token cost visualization.

Deep dive into why coding Agents differ: perception lets Agents understand projects first, context engineering precisely filters information within limited token budgets.

A systematic AI Agent development learning roadmap covering LLM API calls, ReAct framework, memory mechanisms, and multi-agent collaboration across four stages with timeline and project suggestions.

Deep dive into how the Cosmos Unified Agents Platform solves multi-AI Agent collaboration challenges through shared context and memory mechanisms, and its positioning in enterprise multi-Agent orchestration.
Product ReviewsHands-on review of Manus AI Agent on the DeepSeek tech stack, analyzing task execution, Chinese reasoning capabilities, strengths, limitations, and the potential of domestic LLMs in Agent applications.
TutorialsA systematic breakdown of the AI Agent learning roadmap covering core architecture, ReAct/CoT paradigms, multi-agent collaboration, and Prompt optimization across four stages with quality resource recommendations.
TutorialsDeep dive into why Andrew Ng's Agent AI course went viral, covering the five-module agent architecture breakdown, course highlights, target audience, and learning tips for developers.
35 Lines of Prompts Let Codex Auto-Opt…
An OpenAI employee used just 35 lines of prompts to have Codex analyze 30 days of work history, identify repetitive tasks, and generate reusable automated Skills. Combined with screen reading and long-term memory, Codex is becoming a proactive workflow optimization agent.
Dyad: A Free, Open-Source AI Full-Stac…
In-depth review of Dyad, an open-source AI full-stack builder. Supports local execution, multiple AI models, and component-level editing. A free, privacy-first alternative to Lovable and Bolt.new.
TutorialsDeep dive into the Three-Layer Pyramid Model for Agent development, covering autonomous agents, collaborative multi-agent systems, and universal orchestration agents with a complete learning path from beginner to industrial-grade deployment.
TutorialsA complete beginner's guide to LLM application development: learn the three key directions (API calling, RAG, Agent), master frameworks like LangChain, and follow a step-by-step learning path to become an AI application developer.