2697 related articles
Product ReviewsDeep dive into AnythingLLM, a privacy-first, zero-config local AI productivity platform. Supports RAG document chat, multi-model integration, knowledge bases, and AI Agents with nearly 60K GitHub stars.
Product ReviewsDeep dive into LibreChat, an open-source self-hosted AI chat platform supporting GPT-5, Claude, Gemini, DeepSeek and more, with MCP protocol, Code Interpreter, Agents, and enterprise features. 36,500+ GitHub stars.
Product ReviewsDeep dive into Cube Studio, Tencent Music's open-source one-stop AI platform, covering architecture design, distributed training, large model fine-tuning and inference, and domestic chip adaptation.
TutorialsDatasette creator Simon Willison debugged an OpenStreetMap display issue, uncovering CAPTCHA and Referrer-Policy conflicts, then built a plugin fix using GPT-5.5 and Codex.
Product ReviewsIn-depth guide to LibreChat, the open-source AI chat platform with 36K+ Stars. Covers multi-model aggregation, MCP protocol, Agents, Code Interpreter, Docker self-hosting, and comparisons with alternatives.
Expert OpinionsAnthropic co-founders Dario and Daniela Amodei join a rare public conversation moderated by CPO Ami Vora, discussing Claude's evolution, AI safety advances, and Anthropic's competitive strategy.
Tech FrontiersClaude Platform is now GA on AWS, offering enterprises the complete Claude API with IAM-native auth, unified billing, and EDP committed spend credits.
Tech FrontiersA comprehensive guide to Anthropic's Claude Managed Agents: core capabilities including Advisor Strategy, code execution, and web search, plus comparisons with third-party Agent frameworks.
ResearchFirst wet-lab comparison: 6 LLM Agents vs 9 human teams in TREM-2 Binder design show no significant Hit Rate difference (P=0.83). Analysis of tool convergence, in-silico bottlenecks, and designer transformation.
Deep DivesOpenAI Codex has evolved from a coding tool into a general-purpose AI agent covering project management, information synthesis, and personal automation. Deep dive into real usage, /goal mode, enterprise security, and tips.
Deep DivesIn 2026, the AI industry shifts from generative to Agentic AI. Deep dive into GPT-5.5 agent capabilities, Claude's autonomous learning, Physical AI deployment, DeepSeek V4, inference optimization, and the global AI competition landscape.
TutorialsOpenAI open-sources GPT-OSS (20B/120B) with MOE architecture and native FP4 precision. Run O3-level reasoning on a single RTX 4090. Full deployment guide for Ollama, vLLM, and more.
TutorialsA practical guide to AI Agent prompt engineering using a three-layer architecture: System Layer, Input Layer, and Action Layer — with n8n examples.
Product ReviewsFull hands-on review of HIX AI's all-in-one AI Agent platform covering AI presentations, Seedance 2.0 video generation, 4K image creation, and integration of top models like GPT-5.4 Pro and Sora 2 Pro.
Deep DivesA clear breakdown of five core AI programming concepts — Prompt Engineering, Context Engineering, Agent, Skill, and Harness Engineering — with real-world use cases and advice for indie developers.
Product ReviewsIn-depth review of MeMo, an open-source AI Agent platform. Covers long-term memory, MCP protocol, multi-Bot container isolation, omni-channel deployment, with setup tutorials and usage tips.
ResearchAlibaba Mama's Skills-Oriented Programming methodology uses three-layer Skill structures, progressive disclosure, and four-layer anti-corruption systems to achieve 90%+ code generation accuracy for Code Agents in complex enterprise codebases.
TutorialsDeep dive into Anthropic's Building effective agents guide: workflow vs. agent distinctions, the technical selection pyramid, and framework pitfalls for building efficient LLM agents.
Deep DivesDeep dive into Google's A2A protocol core mechanisms (Agent Card, Task, Transport), comparing A2A vs MCP roles, and tracing the evolution from tool calling to multi-agent team collaboration.
Industry InsightsDeep analysis of 5 common pitfalls in AI-generated test cases and how Agent+Skill platforms solve them with automated requirement splitting, precise generation, and end-to-end test execution.