Have you ever built an AI automation that felt like a house of cards? You spend hours perfecting a workflow in a tool like n8n, it works beautifully a few times, and then… it breaks. The AI returns text in a slightly different format, a list becomes a paragraph, and the whole sequence grinds to a halt. It’s frustrating, and it can make you feel like AI automation is more trouble than it’s worth.
I’ve been there. You ask the AI for ten different things, and it spits back one giant, unpredictable blob of text. Trying to use that blob in later steps is a nightmare. But what if you could force the AI to give you exactly what you want, every single time, in a perfectly organized format?
In a recent Future Fiction Academy class, I walked authors through my n8n workflow for starting in a new genre, and we hit on a technique that is an absolute game-changer for making your AI workflows reliable and powerful. It’s all about getting structured output, and it will change the way you build your automations.
The Problem: The Giant Blob of AI Text
When I’m doing genre research, I want to know a lot of things all at once. I’ll prompt the AI for plot structure, pacing expectations, common tropes, character archetypes, heat levels, subplot balance—the list goes on.
Initially, the AI would give me a beautifully written, blog-post-style response. The problem? It was all one big chunk of text.
Later in my workflow, I might have a step where I’m creating characters. For that step, I only need the “Character Tropes and Archetypes” information from my initial research. But I couldn’t easily grab just that piece. My only option was to feed the entire genre research blob into the character creation prompt and hope the AI could find the specific part it needed. This is inefficient and, worse, unreliable.
The Solution: Forcing the AI to Get Organized
This is where a powerful feature in n8n comes in. In the LLM node, there’s a toggle for “Required Specific Output Format.” When you turn this on, a little field appears that lets you define exactly how you want the AI to structure its response using JSON.
Now, don’t let the term “JSON” scare you. You don’t need to be a coder to use this. Think of it as giving the AI a set of labeled boxes to put its answers in. Instead of one big messy pile of text, you get neat, individual packages of information.
As I explained in the class, “It creates each of those 15 [research points] as a separate little output that I can drag and drop in any of the future prompts. So I don’t have to just say, ‘Hey, look at this giant blob of text.’ I can say, ‘Hey, just look at characters.’”
This simple switch transforms your workflow from fragile to robust.
How to Get Structured Output in Your Workflow
Let’s walk through exactly how to set this up, using my genre research workflow as an example.
1. Define Your Data Points
First, in your prompt, you’ll ask for all the information you need. But then, you enable that “Required Specific Output Format” toggle. In the JSON field that appears, you’ll create labels for each piece of information you asked for.
It looks something like this: You tell it you want a label called plot_structure and then you give it an example of what that output should look like. Then you create another label for pacing, another for tropes, and so on.
A pro-tip I shared in class: “All I did was run this prompt once… and then took the output and filled it in here [as the examples].” This teaches the AI the exact format you’re looking for.
2. Let the AI Fill in the Blanks
When you run the workflow, the AI will now generate its response and neatly file each piece of information under the corresponding label you created.
Instead of one output from the node, you get a dozen or more. Suddenly, you have individual data points like:
plot_structurepacingtropescharactersheat_level
3. Drag, Drop, and Dominate
Now, for the magic. In any later step in your workflow, you can grab only the specific piece of information you need. When I’m building my character blueprints, I can drag the characters output directly into the prompt. When I’m creating the outline, I can pull in the pacing and plot_structure outputs.
Each step gets only the precise information it needs, making your prompts cleaner, more focused, and dramatically more reliable. This is how you build complex, multi-step automations that work every single time.
This one technique—moving from a single blob of text to structured, individual outputs—is the key to unlocking the next level of AI-powered writing. It allows you to build sophisticated systems that can generate everything from a character’s core wound to a 20-chapter outline, all from a single form input. It’s about taking control and making the AI work for you, not the other way around.
Ready to stop wrestling with your automations and start building powerful, reliable writing systems? This is the kind of deep-dive, practical strategy we teach every single day inside the Future Fiction Academy.
If you’re already an Accelerator or Mastermind member, you’re going to want to check out our class 319- Write in a New Genre Breakdown where Stacey goes over how all of this works! If you want to go from experimenting with AI to truly mastering it, come join us in the Accelerator and see how far your stories can really go.
