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.
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
Your Cheat Sheet for AI Engineering Interview – Questions and Answers.
A Swift reimplementation of a Claude Code-style coding agent, built stage by stage to explore what makes coding agents work
Learn it. Build it. Ship it for others.
📚 Two books on harness engineering — the design philosophies behind Claude Code & Codex: constraints, query loops, context governance, multi-agent verification. harness-books.agentway.dev
The definitive OpenAI, Claude, MCP, Harness, Evals, and Production Agent Systems learning roadmap.
Context Engineering: Build Consistent, Accurate, Predictable AI Systems
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.
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
Find · Leverage · Optimize · Win — an evidence-led SEO playbook for the AI-search era. 72 docs · 42 AI prompts · 27 diagrams · 15 sourced 2026 stats. CC BY 4.0.