50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.

Your Cheat Sheet for AI Engineering Interview – Questions and Answers.

📚 Two books on harness engineering — the design philosophies behind Claude Code & Codex: constraints, query loops, context governance, multi-agent verification. harness-books.agentway.dev

Bilingual (中文+EN) ML / LLM / diffusion / agent interview cheat sheets for AI 秋招 — generated by ARIS /interview-cheatsheet, rendered by /render-html into single-file HTML, reads anywhere — plus a CV→DBLP-fact-checked academic homepage generator and hand-authored long-form blogs 🌱

The definitive OpenAI, Claude, MCP, Harness, Evals, and Production Agent Systems learning roadmap.

All my YouTube tutorials. Everything here is free - but please follow me on YouTube if you find these helpful.

Open-source cookbook for the Stormy Social Data API and MCP server (Model Context Protocol) — one REST API for the TikTok API, YouTube API, Instagram API, LinkedIn API, X (Twitter) API and Reddit API. Search creators, resolve profiles, read posts and find verified emails from Claude, Cursor, Codex, ChatGPT or curl. One key, no scrapers.

A Swift reimplementation of a Claude Code-style coding agent, built stage by stage to explore what makes coding agents work

Labs to explore AI Models, MCP servers, and Agents with the AI Gateway powered by Azure API Management and Microsoft Foundry 🚀

Build a Claude-Code-shaped agent harness from scratch. 7-week course, 20 chapters, ~5,000 lines of Python, 42 tests, 3 LLM providers, no frameworks.

Context Engineering: Build Consistent, Accurate, Predictable AI Systems

A comprehensive set of samples of creating and using MCP servers and clients with .NET

An MCP Multimodal AI Agent with eyes and ears!

From Java Dev to AI Engineer: Spring AI Fast Track

Build an agentic RAG app from scratch by collaborating with Claude Code. 8-module course covering hybrid search, reranking, text-to-SQL, subagents, and more. React + FastAPI + Supabase.

This repository contains hands-on projects, code examples, and deployment workflows. Explore multi-agent systems, LangChain, LangGraph, AutoGen, CrewAI, RAG, MCP, automation with n8n, and scalable agent deployment using Docker, AWS, and BentoML.

The Developer's Guide to AI - A Field Guide for the Working Developer

A set of MCP security checklists and guides for agents and MCP servers.

Quarkus LangChain4J Workshop that demonstrates both single AI service capabilities and Agentic AI orchestration

Example implementation of MCP Streamable HTTP client/server in Python and TypeScript.