No-code and low-code AI automation platforms as a real production path — workflow fundamentals, where an AI Agent node actually fits, practical automation patterns, error handling under real traffic, and when to graduate to custom code.
Platforms like n8n and Make.com let engineers assemble real, production-capable AI automation visually, connecting triggers, nodes, and the data flowing between them without writing a full custom codebase. This module builds the workflow-design fundamentals using this studio's own n8n guide as the concrete reference, then draws a precise line between a workflow that merely has an AI step in it and one where an AI Agent node is genuinely making its own routing decisions — the same agents-versus-workflows distinction Module 8 covers, applied directly to a no-code canvas.
By the end of this module you should be able to design a document-processing, ticket-routing, or scheduled-reporting automation with real retry and backoff logic instead of a happy-path-only design, and make an honest, non-ideological call about when a workflow's scale or risk profile means it's time to graduate to custom code. Module 17 (Troubleshooting) picks up immediately after this one, covering what actually happens when these automations fail in production.