71 related articles

A 6-week systematic learning path for frontend engineers transitioning to AI Agent development, covering core architecture, ReAct, multi-agent collaboration, RAG integration, and deployment.

OpenAI releases GPT-5.6 with Sol, Terra, and Luna models plus ChatGPT Work execution environment, shifting AI from chatbots to autonomous multi-agent workflows that directly operate local files and business systems.

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.
Human-Centered AI: Real-World Implemen…
An MSR workshop reveals the truth about AI deployment: from a $20 corneal diagnostic device to expert-in-the-loop chatbots, researchers share real-world experiences of AI in healthcare and design within resource-scarce environments.

Why does AI-generated UI all look the same? Designer SEN open-sourced a Skill called Taste that uses a four-agent pipeline to reverse-engineer website "taste" into verifiable design principles called Taste DNA.
DeepTutor: An Open-Source AI Tutoring …
DeepTutor is an open-source lifelong personalized AI tutoring system from HKUDS with 26,000+ GitHub stars. Explore its knowledge tracing, RAG, and multi-agent architecture.

RL3 is a zero-code, browser-based reinforcement learning platform featuring drag-and-drop environment design, visual reward configuration, and Q-learning/PPO training. Built by an indie developer over 15 months to make RL accessible to everyone.
Anthropic Open-Sources CWC Workshops: …
Anthropic open-sources cwc-workshops on GitHub — a TypeScript-based, structured workshop covering Prompt design, Tool Use, and Agent orchestration to help developers master Claude integration.

Squint open-source research enables a $120 SO-101 arm to search beyond its camera FOV using 16×16 pixel input, achieving 100% success in 24 min on an RTX 4060.

OpenAI's new model reportedly proved the Cycle Double Cover Conjecture in under an hour using 64 parallel sub-agents. The real lesson? In the AI era, knowing how to ask the right questions matters more than knowing how to calculate.

LLMs answer questions; Agents actually get things done. This article breaks down the differences between LLMs, Chatbots, and Agents, explains the perceive–think–act architecture, and maps real-world use cases across education, finance, and healthcare.

A deep dive into Harness architecture in enterprise Agent projects, covering MCP protocol, sandbox isolation, multi-model scheduling, and ASGI deployment — key topics for LLM job interviews.

OpenAI merges ChatGPT and Codex into a super app and releases three new GPT-5.6 models: Sol, Terra, and Luna. A deep dive into four hands-on workflows—Computer Use, Loops, and multi-threading—for the AI agent era.

Anthropic's open-source Claude Cookbooks project offers runnable Jupyter Notebook examples covering RAG, Tool Use, multimodal processing, and more—helping developers master Claude API best practices.

A systematic AI Agent development learning path covering fundamentals, prompt engineering, tool calling, multi-agent collaboration, and hands-on practice with LangChain, CrewAI, and Dify.

A user's American Express card was auto-charged 171 times by an AI service, totaling nearly $1,800 with no warning. This article analyzes pay-as-you-go risks and offers practical protection: spending limits, virtual cards, and automation monitoring.

Coze is ByteDance's low-code AI Bot platform for building AI agents without coding. Learn the differences between the domestic and international versions, core feature comparisons, and monetization potential.

In-depth analysis of AI Agent core principles: why LLMs need Agent technology, the evolution from Prompt to RAG to Agent, Agent Tuning methods, and enterprise cost evaluation to help you build enterprise-grade agent applications.

An in-depth look at the three core eras of AI Agent development: reliable tool calling, coherent long-task execution, and autonomous orchestration with metacognition. Helps developers match tasks to model capabilities.

AI Agents are reshaping software development with 42.8% market CAGR. Learn the difference between Agents and traditional AI, plus a complete LangChain-based curriculum to launch your career in intelligent agent development.