
learn-agent
A collection of notes on building coding agents, derived from the production development of the desktop agent Reina, with each mechanism simplified into a zero-dependency, single-file Node.js demo.
It offers a focused, lightweight web-based environment for structured protocol practice without requiring a desktop install, with a clear layout and a hosted build for immediate access.
A browser-based training application for protocol-driven practice, built on the Apex Protocols foundation and designed to support structured learning sessions in a hosted or local setup.
Similar projects matched by category, topics, and programming language.

A collection of notes on building coding agents, derived from the production development of the desktop agent Reina, with each mechanism simplified into a zero-dependency, single-file Node.js demo.

A comprehensive step-by-step tutorial series that teaches AI agents from scratch, covering function calling, agent loops, ReAct, reflection, plan-and-execute, multi-agent systems, orchestration, evaluation, and related concepts like RAG, GraphRAG, and LangChain.
INTACT is an end-to-end JEPA world model that learns an isomorphic intent-to-action interface, enabling search-free direct control for goal-conditioned robot tasks with high success rates after just one epoch of training.