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.
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.
DIO PRO Vitalício Week: Agentes de IA
A comprehensive set of samples of creating and using MCP servers and clients with .NET
The definitive OpenAI, Claude, MCP, Harness, Evals, and Production Agent Systems learning roadmap.
An MCP Multimodal AI Agent with eyes and ears!
Context Engineering: Build Consistent, Accurate, Predictable AI Systems
100 field-tested Claude Code recipes for knowledge workers — prompts, steps, and 6 installable graded skills.
Your Cheat Sheet for AI Engineering Interview – Questions and Answers.
Labs to explore AI Models, MCP servers, and Agents with the AI Gateway powered by Azure API Management and Microsoft Foundry 🚀
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.
📚 Two books on harness engineering — the design philosophies behind Claude Code & Codex: constraints, query loops, context governance, multi-agent verification. harness-books.agentway.dev
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
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 🌱