Explains embeddings — numerical vectors that capture meaning — and the vector databases built to store and search them, and shows why together they power semantic search, Retrieval-Augmented Generation, and long-term memory for AI agents.

How to run Anthropic’s Claude Code CLI inside Obsidian via a terminal plugin, using Agent Skills and CLAUDE.md so the agent manages your vault in Obsidian-native formats.

What an AI agent is, how it differs from a chatbot, its core loop and components (LLM, tools, memory), the ReAct pattern, how autonomy is classified, and the open challenges that still limit reliability.

How to build multi-agent systems with the Deep Agents framework using two primitives — subagents for context isolation and skills for progressive disclosure.

A hands-on guide to Google’s Gemini CLI – an open-source AI agent that brings autonomous tooling into the terminal, with built-in tools, MCP server support, and extensibility for real-world automation.