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Deep dive into Hermes Agent's 7 core features including Kanban multi-tasking, /goal deep execution, and multi-agent architecture, compared with OpenCore's stability and performance issues.
TutorialsCursor engineer Eric shares practical insights on building an AI software factory: automation levels, guardrail design, parallel Agent management, and scaling to 1000+ Agents for 24/7 development.
TutorialsDeep dive into how AI coding Skills work technically, from Function Call to MCP to Skills as sub-agents with on-demand loading, implemented via Spring AI Alibaba.
TutorialsDeep dive into how AI coding Skills work: from Function Call to MCP to Skills as sub-agents with on-demand loading, implemented via Spring AI Alibaba.
Product ReviewsCursor 3.0 evolves from an AI coding assistant into an Agent fleet command center. Deep dive into multi-agent parallelism, Design Mode, and Best-of-N model comparison.
Product ReviewsCursor 3.0 evolves from an AI coding assistant into an Agent fleet command center. Explore multi-agent parallelism, Design Mode, and Best-of-N model comparison.
TutorialsDeep dive into the technical differences between traditional RAG and Agentic RAG, covering offline/online pipeline principles, tool-based autonomous decision mechanisms, and a LangGraph-based Agentic RAG implementation via the ChatBox open-source project.
TutorialsA comprehensive guide to AI Agent development for beginners, covering core concepts, market outlook, LangChain framework, RAG knowledge bases, and hands-on projects to systematically master intelligent agent development skills.
Product ReviewsZed Editor's Windows version is officially released. This free, open-source AI IDE built with Rust features extreme performance, built-in Cloud Code, Gemini CLI, and Codex agents, a native debugger, and real-time collaboration.
Product ReviewsZed Editor's Windows version is officially released. This free, open-source AI IDE built in Rust features extreme performance, built-in Cloud Code, Gemini CLI, and Codex agents, native debugging, and real-time collaboration.
Product ReviewsDeep dive into JCode, an open-source Coding Agent Harness designed for multi-Agent collaboration. Features Agent Memory, Swarm collaboration, multi-Provider access, and self-evolution with just 14ms first-frame latency and 117MB for 10 sessions.
Industry InsightsDeep comparison of Claude Code and OpenClaw AI Agent architectures—from tool governance pipelines and security sandboxes to memory systems and multi-agent collaboration.
Deep DivesA deep dive into Claude Code's core capabilities: understanding codebases, autonomously executing commands, and searching the web. Learn key concepts like context windows and permission control.
TutorialsComplete guide to Hermes Agent's five core pillars: Memory, Skills, Soul, Crons & self-evolution. Covers VPS deployment, Telegram setup, security management & best practices for building an AI assistant that grows stronger over time.
Expert OpinionsAnalysis of context fragmentation in multi-Agent collaboration, comparing memory vs. state management approaches, and how tools like Opal Bridge enable seamless switching between Claude Code, Codex, and other Agents.
Product ReviewsRoundup of 6 developer tools: CodeBurn for AI coding token cost tracking, Mirage virtual file system for Agents, Boring SSH tunnel manager, PeerTrace file tree renderer, DataTab font-based data visualization, and Flu TypeScript Agent framework.
Product ReviewsDeep dive into OpenClaw v2026.5.14: TelLinks real-time voice calls, gateway freeze fix, Telegram message congestion resolution, Agent transparency, DeepSeek V4 Flash config, and 120+ bug fixes.
Product ReviewsIn-depth comparison of OpenClaw and Hermes open-source AI Agent frameworks covering architecture, memory systems, auth, plugins, and channel distribution to guide developer selection.
Expert OpinionsReplit CEO Amjad Massad on AI coding models hitting a ceiling, competition shifting to product engineering, SaaS being replaced by AI Agents, the death of the IDE, and multi-model orchestration.
Deep DivesDeep dive into context engineering as the core of Agent development, covering five context modules, four pain points, and dynamic assembly solutions including compression, hybrid retrieval, multi-Agent architecture, and state machine control.