Update docs/glossary.md

Co-authored-by: Nick Veitch <[email protected]>

docs/glossary.md

@@ -12,7 +12,7 @@ contentType: reference
 * **AI tools**: In an AI context, a tool is an add-on resource that the AI can refer to for specific information or functionality when responding to a request. The AI model can use a tool to interact with external systems or complete specific, focused tasks.
 * **AI vector store**: Vector stores, or vector databases, are databases designed to store numerical representations of information called embeddings.
 * **API**: APIs, or application programming interfaces, offer programmatic access to a service's data and functionality. APIs make it easier for software to interact with external systems. They're often offered as an alternative to traditional user-focused interfaces accessed through web browsers or UI.
-* **canvas (n8n)**: The canvas is the main workflow-building interface in n8n's editor UI. You use the canvas to add and connect nodes to compose workflows.
+* **canvas (n8n)**: The canvas is the main interface for building workflows in n8n's editor UI. You use the canvas to add and connect nodes to compose workflows.
 * **cluster nodes (n8n)**: In n8n, cluster nodes are groups of nodes that work together to provide functionality in a workflow. They consist of a root node and one or more sub nodes that extend the node's functionality.
 * **credential (n8n)**: In n8n, credentials store authentication information to connect with specific apps and services. After creating credentials with your authentication information (username and password, API key, OAuth secrets, etc.), you can use the associated app node to interact with the service.
 * **data pinning (n8n)**: Data pinning allows you to temporarily freeze the output data of a node during workflow development. This allows you to develop workflows with predictable data without making repeated requests to external services. Production workflows ignore pinned data and request new data on each execution.