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Hermes Agent is an open-source self-evolving AI agent framework open-sourced by Nous Research at the end of February 2026. As of early May, it had already surpassed 100,000 stars on GitHub, making it one of the fastest-growing open-source projects of 2026. This lightweight Python-based framework's standout feature is that it "gets smarter with use" — it automatically learns from each task, creates and improves its own skills, and builds long-term memory.

Matt Pocock's Skills project is an engineering skill library for AI coding assistants (such as Claude Code). By modularizing standard software development workflows, it addresses the core pain point of inconsistent quality in AI-generated code.

Many frontend engineers feel a bit confused when first encountering MCP: it sounds like a protocol, acts like an Agent, and discussions are full of Tool, Prompt, Resource, and Skill. But you don't need to digest all these terms at once. Just remember this one sentence: MCP is a standardized way for AI to connect tools, access data, and actually get things done.

code-review-graph is an open-source tool for AI coding assistants. It first builds a structured knowledge graph of your codebase locally, then supplies only the relevant context to the AI — avoiding a full scan of the entire repository on every task. Powered by Tree-sitter to parse ASTs, it organizes functions, classes, imports, call relationships, and test dependencies into a graph structure, and makes it available to tools like Claude Code, Codex, and Cursor via MCP.

Nowadays, my main full-stack frameworks are Next.js 16 and Rails 8. Through using Rails, I came across the officially recommended deployment tool Kamal. I usually use it to deploy projects on Rails and Alibaba Cloud servers. It's very handy and simple, so now I'd like to introduce the concepts and basics of Kamal2 to everyone.

Let's start with a one-sentence summary: Prisma is a modern ORM and data access toolchain for TypeScript/JavaScript.