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·6 min
Hands-On With Hermes Agent's Eight Major Updates: A Complete Guide to AI Automation and Self-Evolution
The Hermes Agent gets a major upgrade with eight new features: native iMessage, parallel background sub-agents, Unreal Engine MCP support, a self-evolving Skill Hub, and more. A hands-on breakdown of the core changes and their real impact on personal AI automation workflows.
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·4 min
TigrimOSR: An Open-Source Agent Framework in Rust with Configurable Agent Loops
TigrimOSR is an open-source multi-agent system written in Rust, supporting full agent loop definition via YAML config files with only 250MB memory usage. A deep dive into Loop Engineering, Rust advantages, and self-hosted Agentic AI.
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·6 min
The Eight-Step Method for Agent Development: A Practical Path from Pitfalls to Production
Many enterprises fail at AI Agents due to choosing the wrong tools and lacking methodology. This article outlines an eight-step Agent development method—from cognitive foundations, scenario selection, hand-writing ReAct, and structured output to Tool Use, RAG, evaluation sets, and production fallback.
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·7 min
Turning Any AI Agent into an Orchestration Hub: A Deep Dive into Multi-Agent Collaboration Architecture
An in-depth analysis of the "any Agent as an orchestrator" design philosophy, exploring the technical implementation of multi-Agent collaboration, context management, and workflow automation.
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·6 min
The Complete Beginner's Guide to Claude Code: From Installation to Advanced Usage
Claude Code is one of the most powerful AI coding agents, running in the terminal to write code, batch operations, build web projects, and more. This guide covers installation, connecting local models via CC Switch, permission modes, CLAUDE.md, Skills, MCP, Subagents, and more.
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·5 min
From Prompts to Harness Engineering: The Evolution of AI Agent Development Paradigms
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.
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·6 min
Skill vs MCP: The Essential Difference Between Two Types of AI Agent Capabilities and How They Work Together
Skill and MCP are two core concepts for building AI Agents. Skill encapsulates task execution methodology, while MCP provides a standardized protocol for connecting external tools. This article breaks down their core differences, abstraction levels, and collaboration.
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·7 min
Geosql: A Vertical Skill Pack That Teaches AI Geospatial Data Analysis
Geosql is a geospatial SQL skill pack designed for AI coding assistants like Claude and Codex, enabling LLMs to accurately generate PostGIS queries and handle coordinate transformations and spatial analysis.
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·7 min
Rowboat: An Open-Source, Local-First Alternative to Claude Desktop
Rowboat is an open-source, local-first AI desktop client positioned as a Claude Desktop alternative. Local data storage and fully transparent code help developers control privacy and workflows.
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·5 min
Claude Cowork Arrives on Mobile and Web, with Max Users Getting Early Access
Anthropic's AI collaboration platform Claude Cowork officially expands to mobile and web, breaking free from desktop-only limits. Max subscribers get early access, with other plans rolling out over the coming weeks.
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·6 min
From Frontend Engineer to AI Agent Developer: A Complete High-Paying Skill Tree Breakdown
Pure frontend roles are shrinking; AI Agent development is the high-salary divide. This guide breaks down the full skill tree for frontend engineers pivoting to AI: TypeScript, frameworks, AI productivity, and Agent core concepts (MCP, Tool Calling, Skill).
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·7 min
Connecting Hermes Agent to MCP: One Protocol to Unify All External Systems
Learn how to extend Hermes Agent's external system capabilities via MCP (Model Context Protocol): setup, whitelist permissions, WSL-to-Chrome bridging, and multi-server orchestration for AI Agent developers.
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·7 min
Gemini CLI: The AI Development Powerhouse in Your Terminal, Ending Tool Fragmentation
Gemini CLI is Google's open-source AI terminal tool that deeply integrates Gemini model capabilities into the command line—supporting code generation, file operations, Shell execution, and MCP protocol extensions, with 1,000 free daily requests.
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·5 min
OfficeCLI: A Command-Line Tool for AI Agents to Read and Write Office Documents
OfficeCLI is a command-line office suite for AI agents, supporting reading and writing of Word, Excel, and PowerPoint files—enabling efficient Office document automation without complex glue code.
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·7 min
The Complete Guide to OpenCode: Installing, Configuring, and Using the Terminal AI Coding Assistant
An in-depth guide to installing, configuring, and extending OpenCode, the terminal AI coding assistant. Covers desktop and WSL installation, model config, MCP integration, and custom Agents.
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·7 min
Spring AI 2.0 in Practice: A Beginner's Guide for Java Developers Building AI Agents
A complete Spring AI 2.0 guide for Java developers covering unified API abstraction, RAG, tool calling, MCP protocol, and enterprise projects to build AI Agents.
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·2 min
MCP Protocol Deep Dive: The Unified Standard and Practical Guide for Agent Development
Deep dive into MCP (Model Context Protocol): core principles, communication mechanisms, and security design. Learn how MCP replaces Function Calling and enables remote agent-tool integration.
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·6 min
Java Developer's Guide to AI Application Development: Building an Airline Intelligent Customer Service System
A practical guide for Java developers to build AI apps without switching to Python. Learn LangChain4j, RAG, Function Calling, and MCP through an airline customer service project.
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·6 min
herder: A Terminal Multiplexer for Multiple Coding Agents — Say Goodbye to Session Management Chaos
herder is a terminal multiplexer for coding agents like Claude Code and Codex, combining tmux power with mouse support, agent state awareness, and session persistence for efficient multi-agent workflows.
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·5 min
Cursor Reshapes AI Programming: Cloud Agents, the Origin Platform, and a Custom-Built Foundation Model
Cursor launches three major products: cloud agents on mobile, Origin — an agent-native Git platform challenging GitHub, and a custom foundation model with 10-20x compute. AI coding enters the Agent-First era.
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