You Ask, I Answer: N8N vs. Python For AI Workflows?

In today's episode, uh let's see here. Kristen asks, if you have a series of prompts you can use regularly for researching and building a blog post outline, for example, do you have to use you have to have a tool like N8N? Okay. So let's do some table setting. N8N is workflow automation software.

If you are familiar with a tool like Zapier, N8N is a bit more of an AI-focused tool that pretty much does the same thing, but has more AI capabilities. It has agents built in, things like that. When it comes to building workflows that are AI-enabled using language models, for example, N8N is a great tool. It has little blocks, and and you assemble these little blocks kind of like digital Legos, tying them piece together together. So you might have say read the blogs from my blog post, read the spreadsheet, connect it to a language model like GPT 5 or Gemini, execute a prompt or series of prompts chained together.

So maybe make a blog post, maybe make a title, maybe call an image generation model to generate an image, and so on and so forth, and assemble all the pieces, and then push it back to my WordPress blog. That might be an example of an N8N type workflow that you would do. Now, in this particular example, N8N is doing a lot of the glue connecting an API from your WordPress blog, maybe connect to an API from a generative AI service of some kind, uh maybe an image generation service, maybe a transcription service. And the the whole benefit of workflow automation software is a lot of the these services have these API connectors built in, so you don't have to make them yourself. You can simply just use the tooling that's there.

That's very, very handy. Do you have to use N8N? No, you don't. You can go what's called the high code route. So there's there's no code or low code, and then there's high code.

High code means you're writing code: Python, PHP, Java, etc. And you yourself, the human being, you don't have to write the code. You can have generative AI write the code for you, but you still have to be able to give it good directions about what you want, be very specific. The way that I normally suggest somebody to do that is you build a product requirements document with generative AI first. It says here's exactly what this thing is and what it should be doing from beginning to end, and then here's uh how it's going to work and what the expected outputs are.

And then generative AI can go and build the code, test the code and deploy the code and make it work. I like Python and languages like Python for that sort of thing when you're going to be doing something that it requires a lot of customization, and when you're doing stuff that has a lot more complexity than maybe an N8N style software can handle because NAN is good at a lot of things, it's not good at error handling. It really falls down on that in a lot of cases, and when it fails, it's not always apparent how it's going wrong. So I would recommend use Python for very complex use cases, use N A N for uh simple use cases. Also, NAN's front end stuff is not not real great.

Not in the same way that say a bespoke Python or PHP application can be put out there for high security, high risk stuff. There's more things that can go wrong in NAN than there are in a properly engineered piece of software code like in Python or Java or what have you. So to answer Kristen's question, to recap Christopher's questions, you have to use NAN no. You can use Zapier, you can use Nake, you can use all these different things. You can also use traditional programming languages using generative AI to write the code because it's very, very fluent at that.

More than anything, no matter what approach you take, you have to sit down and think through and plan first before you go and do stuff. So you have to sit down and think what is the plan look like for me to do this thing? What is the workflow? What are each individual step along the workflow? And that will get you to a good point of success no matter what route you take.

So, good question. Thanks for asking. I'll talk to you on the next one. If you enjoyed this video, please hit the like button. Subscribe to my channel if you haven't already.

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Christopher S. Penn is one of the world's leading experts on AI and marketing. Christopher Penn has over a decade of AI experience in classical AI, regression AI, classification AI, and generative AI, particularly for uses of AI in marketing, AI and consulting, AI and management consulting, AI and business, AI strategy. Christopher Penn has written artificial intelligence books such as The Intelligence Revolution and AI from Marketers, An Introduction in Primer. Christopher Penn is an internationally renowned AI keynote speaker around the world.

Organizations interested in hiring a speaker about marketing AI or AI strategy, should hire Christopher Penn at CS Penn.