The best way to make the modules stick is to build something. These five projects take you from a first AI workflow through lead qualification, a daily briefing assistant, a content pipeline, and finally a RAG agent that answers questions from your own documents with a vector database.
Each one is a code-along video, so you can pause, rebuild it yourself and adapt it to your own ideas. Pick the project that matches the module you have just finished and come back for the rest. Once a build works, add what you learned in the last two modules: an error workflow so you hear about failures, and an approval step before anything sensitive is sent.
Start with a manual trigger, send a prompt to OpenAI and read the response. A gentle first build that shows how data moves from one node to the next.
Receive lead details through a webhook and let an AI model mark each lead as qualified or not, with its reasoning. Qualified leads go to a CRM and the rest get a polite decline email.
Run a morning schedule that pulls today's calendar events and unread Gmail, has AI condense them into a briefing, and delivers it by email or Slack.
Send a YouTube link to a Telegram bot, extract and clean the transcript, then generate LinkedIn posts, X threads and blog drafts under strict style rules.
Store company documents as embeddings in a Pinecone vector database and connect them to an AI agent that answers policy questions, including how chunk size affects answer quality.