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Just have a look at their landing page, it made me shed a tear.
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I noticed this pretty early on when AI first started taking off.
I could see exactly what I should use it for and exactly what I shouldn’t use it for.
And if you already know what to use AI for, that’s fine.
But I’m going to give you three rules, or maybe three questions, that you can use instead of just trying it out and seeing if it works.
Generally, these rules apply.
Rule 1: Can it be automated without AI?
And obviously, I don’t mean automated with AI.
I mean automated with something like n8n, code, Python, or anything that can run the task without needing an AI model.
If it can be automated without AI, you probably should automate it without AI.
At least right now.
Eventually, maybe we’ll have open-source models that are cheap enough and good enough to use for everything.
But right now, if you can do it without AI, it’s usually faster, cheaper, and more reliable.
Now, if AI makes the result better, but the task can still be automated without AI, then it becomes your choice.
You can pay for a better experience or better results.
But if you’re not exactly on the rich side yet, and you’re still starting out, I’d recommend automating it for free or near-free first.
Rule 2: Does it need to be personalized?
This applies to a lot of different things, but the example I’ll use here is emails.
You can automate emails all you want.
But you can’t really automate personal emails the same way.
Okay, technically you can.
But it’s harder, and to be honest, you’re probably not going to get the best results if you do it purely with normal automation.
For cold email, the best setup is usually mixing automation and AI.
Use automation to scrape.
Use automation to send.
But use AI to personalize the actual message.
That’s just one example, and there are many others.
But the question is:
Does this need to be personalized?
Does it need to be specific to a person, a situation, or a context?
If yes, then AI is probably useful.
Rule 3: Does it need to be the same every single time?
If you need the same result every single time, you might not want to use AI.
I’m not saying AI can’t give you similar results.
It can.
But at the end of the day, AI is statistically guessing what it should say based on a lot of data.
So maybe it does the same thing 10 times in a row.
But will it do it 1,000 times in a row?
Probably not perfectly.
Some of the outputs are going to be different.
And for something like personalized messages, that’s actually fine.
It’s better if they’re not all exactly the same.
You want them to be diverse.
But for something where the result needs to be strict, repeatable, and identical every time, automation is usually better.
This also connects back to rule one.
If it can be automated, use automation.
That’s what automation is perfect for.
But if it can’t be automated, and you still need the same result every single time, you can try AI.
Just know that if the task is very strict, AI might not be the best tool for it.
So the simple version is:
Can it be automated without AI?
Does it need to be personalized?
Does it need to be the same every single time?
Those three questions will usually tell you whether AI is the right tool or not.
Anyway, if you like this kind of thing, I write a weekly newsletter every Monday about AI.
I read through everything and tell you what actually matters.
A lot of AI newsletters talk about the news, but they don’t leave enough out.
They just cover everything.
And they also miss the part of the news that actually matters.
For example, I saw a lot of people talking about the OpenAI vs. Sam Altman court case.
But I didn’t see many people talking about how Sam Altman needed to drop GPT-5.5 before the court case to boost his numbers.
That’s the kind of perspective I try to give.
Not just “here’s what happened.”
More like:
“Here’s why it actually matters.”
So go to the comments below and have a look.
You don’t have to sign up the first time.
Just check it out.
I’m pretty sure you’ll like it.