AI is a Recipe: The Secret to Consistent, High-Quality Results
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Are you tired of spending more time editing the generic blandness out of AI's work than it would've taken to write it yourself?
Most people are frustrated because they see AI as a magical black box. The truth is, AI is not a chef—it's a recipe book. And if you want to stop wasting hours on editing, you need to be the one who writes the recipe.
If you look at the world of experts, they are all, in a way, presenting their recipes for something. The best recipes that get the best results are the ones that... people will adopt. They are very specific in a set of steps you can follow.
You need to look at your work the same way. You want to break those down, each of those down into a recipe, because it works very, very well with AI.
The High Cost of Inconsistency
Just like cooking, if you try to take a general set of things and feed it into any of the different frontier models—like Claude or ChatGPT—they each give different results.
It’s very, very similar to when I try to make focaccia, which is something I enjoy from my trips to Italy. Even following the recipe exactly, I end up with little differences because of the humidity, the flour, or how you mix that.
It's very difficult to overcome that. Your output will be unpredictable, making your work look inconsistent, costing your company valuable, billable hours, and destroying your professional credibility. If you want consistent, high-quality results, you must stop winging it.
The answer? You must create your own (clear, simple approach)[/best-ai-courses-non-technical] for the things you do repeatedly with AI.
Deconstruct Your Job into Ingredients and Instructions
If you'll think of your work as a recipe, you have to nail down two non-negotiable parts:
- Ingredients (The Inputs): This is the context AI needs. Your job is to gather and structure the data it needs to start. The inputs would be your ingredients.
- Instructions (The Transformation): This is the precise direction and formatting the AI needs to create the final output.
A Real-World Recipe: The Employee Manual
Let's say you have to create or update an employee manual. This is a perfect task because these are quite large documents and you need input from many different departments.
- Ingredients: You might need a previous version, interviews with different leaders, or notes you've taken. You might need "these six documents or those ten or these fifty documents."
- Preparation: You might transform whatever format they give you into a markdown document to ensure consistency.
- Instructions: These are the instructions you're going to give the AI: make sure the inputs are consistent, and the output needs to be like "ten pages and have like these sections," or "a hundred pages or whatever."
The Biggest Mistake: Why You Have to 'Throw It Out'
The biggest fault that I see—and it is very similar to cooking—is it's like if you just go out and just kind of like wing it.
If you try to just throw a bunch of different documents at the AI and say, "make an employee manual out of this," you might find that you then spend five days completely frustrated because the output is unusable and you have to start over. This massive waste of time almost all comes from the fact of not doing a good recipe in the beginning.
Before: You are spending hours editing generic blandness out of the AI's work.
After: You are giving the AI a clear recipe and you are likely to have a very good result.
The Next Step: Get the Deconstruction Template
The goal isn't just to save time. It's about recognizing the window of opportunity you have right now to stand out with AI. Building a clear recipe is how you finally fully realize your potential for your work, delivering the impact you know you're capable of.
If you are tired of winging it, the next step is simple.
I’ve created a low-cost tool called the Deconstruction Template. It's five dollars, and it walks you through the exact process of identifying the 'Ingredients' and 'Instructions' for one of your high-value job responsibilities. It is the simple foundation you need to stop wasting days on frustration and start building reliable, repeatable approaches with AI.