Because: - I can write JavaScript inside nodes - When each event is a JSON blob, it’s trivial to handle data - You can break down arrays/lists into series of

Because: - I can write JavaScript inside nodes - When each event is a JSON blob, it’s trivial to handle data - You can break down arrays/lists into series of discrete events, and switch them along different paths with simple filtering logic - You can build sub-flows and re-use them trivially. - You don’t have to worry with doing HTTP requests or handle database connections (you just receive the request results as a JSON object or create an object you send to a database node So for me a basic flow is [template node with prompt]->[LLM API call]->[parse and branch out depending on outcome]->[store output], and I only write two snippets of JS inside a couple of nodes. I do have Jupyter on my stack (another stack, too, with GPU access), but it tends to be linear, messy and impossible to leave running as a service. My Node-RED stuff is effectively “testing in production” and exposing HTTP endpoints as well, and I switch by prod/test by linking the right nodes… But yeah, when I’m happy with the prompt or the flow I look at it and write some actual code. Just not in Jupyter.