RAG
GenAI Integrations
Learn how to connect generative AI to real systems: retrieval-augmented generation over your own data, custom MCP servers that give agents safe access to your tools, and autonomous agents orchestrated to do useful work. Course Content Architecture of GenAI integrations: models, embeddings, retrieval, and orchestration Building a RAG pipeline over your own documents (vector database, chunking, retrieval) How the Model Context Protocol (MCP) works and building your own MCP server (FastAPI / Node.js) Configuring, deploying, and testing autonomous agents (OpenClaw and similar orchestrators) Keeping integrations safe and affordable: prompt boundaries, cost control, evaluation Formats & Pricing The same course, in three formats — pick what suits you:
Drupal Pro Developer
Advanced Drupal architecture for developers who already know the basics. Build custom modules the right way, integrate external services, and deploy a modern RAG chatbot into the Drupal admin — with an AI agent accelerating the work and a code review discipline to keep it correct. Open source. The course builds on a public docker-compose stack for Drupal 11 — a multi-stage PHP 8.4 image with Xdebug in the development layer and without it in production, switched by a single variable. Exactly the setup we deploy through the CI/CD pipeline on the course. Docker is part of the repository, next to the Drupal codebase, so the environment is versioned by the same git history as the application and cannot drift from it.