This level assesses a user's fundamental knowledge of n8n and Generative AI. The questions are designed to confirm a basic understanding of the core definitions and the primary components that constitute a workflow and a generative model.

The questions in this section cover what n8n is, the purpose of a workflow, and the primary node categories—triggers, transformations, and actions.5 It also explores the high-level purpose of Generative AI and Large Language Models. At its core, Generative AI is defined by its capacity to create new content and ideas, including text, images, and videos, based on patterns learned from existing data.8 This stands in contrast to traditional analytical AI, which is designed to classify or predict.

The progression from traditional automation to the fusion with Generative AI marks a paradigm shift. Historically, business process automation tools relied on rigid, rule-based logic. For example, a workflow might be configured to if (email.subject == 'Invoice') then (save attachment). The introduction of an AI-powered node fundamentally changes this. A workflow can now handle unstructured, variable input, such as a natural language email, and perform a semantic transformation. The workflow can be prompted to "identify invoices that need to be paid" or "summarize the content of the email" and intelligently extract the necessary data, even if the input format varies. A Webhook node is a perfect example of this, as it acts as a flexible entry point for diverse external data from services that may not have a pre-built trigger, enabling an automation to respond to virtually any event.5 This qualitative leap is central to understanding the value proposition of n8n's advanced capabilities.