GenAI Engineering
From Python fundamentals to production-grade AI systems — tokens, RAG, tool use, MCP, and agentic SDKs.
Model Context Protocol — The Universal Language for AI Tools
Architecture · History · Configuration · Real-World Examples
A deep-dive into Model Context Protocol — the open standard that connects AI models to any tool, database, or service. Covers architecture, JSON-RPC internals, configuration, real-world examples, and CI/CD integration.
GenAI Engineering — Phases 1–3
Python · APIs · Tokens · Prompting · RAG · Embeddings
A complete, interactive curriculum from Python fundamentals to production-grade AI systems. Phase 1: foundations. Phase 2: LLM basics (tokens, context windows, prompting). Phase 3: RAG (embeddings, chunking, retrieval). Includes live simulators for each concept.
GenAI Engineering — Phases 4–6
Tool Use · MCP · Agent SDKs · LangChain · LangGraph
From chatbot to action machine. Phase 4: Tool calling fundamentals. Phase 5: Model Context Protocol (MCP) — the USB-C of AI. Phase 6: OpenAI Agents SDK, LangChain, LangGraph, and LlamaIndex. Includes animated flow diagrams and interactive workflow builders.
Ollama: Run AI Locally
Local LLMs · Installation · Model Catalog · Harness Tools · Codex CLI
A complete beginner-friendly guide to Ollama — the open-source runtime that lets you run LLMs like Gemma, Llama, and Mistral entirely on your own hardware with no cloud, no API keys, and no data leaving your machine. Covers architecture, installation, Modelfiles, system requirements, pros and cons, and using Ollama as a backend for harness tools like Codex CLI and Continue.dev.