😬 We’re Failing Because of This

What do you think makes a great AI product?

Most would say one that can do it all.

Or, something with a lot of features and flexibility to deliver what you need, when you need it.

But I'm seeing the exact opposite in my client work right now.

The AI products getting real traction are not the ones trying to do everything. 

They are the ones solving one specific problem for one specific type of person.

That is the paradox.

The narrower the AI, the more valuable it often becomes.

That reminded me of a simple rule we use in marketing all the time:

"Speak to everybody = speak to nobody."

This applies to AI more than almost anything else. If you're building a custom AI, an AI product, or any business in general, you need to hear this.

Walk with me, because there's a lesson here that you can apply to your own business, regardless of what your product or service is.

📉 The "AI for Everything" Trap

A recurring issue I see with broad AI is that it sounds amazing on paper, but fails in practice.

Key Facts

• 📉 50% Failure Rate - Gartner just reported that at least half of all generative AI projects are abandoned after the proof-of-concept phase - due to unclear business value, poor data, or escalating costs.
• 💸 $200M Profit Uplift - Meanwhile, SymphonyAI tracked vertical (highly focused) AI deployments in retail and verified a $200 million profit uplift across 80+ real-world deployments.
• 🎯 77% Better Accuracy - In financial services, those same focused AI tools reduced false positives by 77% compared to general systems.

Recently, I watched a team realize their AI experience had become way too broad.

Users were bringing hundreds of different topics to the tool - it sounds impressive, but it actually diluted the experience.

It made the product harder to position and harder to sell.

The fix wasn't to add more capabilities.

It was to narrow the focus down to just a few.

Humbly I'm going to take one for the team here - because I'm human too. Their Ads lead called this out, and he was totally right. 

I didn't see it because I was so focused on getting growth moving that we forgot to stop and measure the data early. 

Once we looked at usage it was clear we had too many expectations of how to use it - and no clear path for “the” usage of it.

When the promise of your AI is too wide, a few things happen immediately:

• The buyer doesn't know if it is actually for them.
• The first prompt feels high-friction because they don't know where to start.
• The product lacks a clear "job."
• The messaging becomes generic.
• Your performance data gets muddy because too many use cases are mixed together.

If your AI is for everyone, nobody knows what to ask it. Nobody knows what result to expect. And nobody knows if it is really for them.

If a customer needs a paragraph to understand your AI, it is probably too vague.

🚪 The Niche Era

You've heard it in marketing.

Social media.

Messaging. (I talked about this in my newsletter “AI Will Bury You For This” a few weeks ago 👉 here.)

And it's true for AI as well.

We're in an era where people are looking for specific products and solutions to specific problems.

I searched through the AI notes of my recent meetings just to prove this personally. 

The highest-performing examples were all tied to defined niches, clear pain points, and obvious user intent.

In one wellness-related discussion, the opportunity was not "general AI health help." 

That's wayyyyy too broad. 

The winning angle was a narrower entry point connected to food, budget, and practical decision-making - because that mapped exactly to what their audience already responded to.

AI works best when it enters through a door the customer already wants opened.

The goal is not to build an AI that can answer everything. It is to build an AI that solves something people already care about.

Because narrower AI actually improves your positioning. 

It clarifies the promise. It reduces onboarding friction. It gives you cleaner data to iterate on. 

And it creates much better marketing hooks.

Focused AI is easier to sell because the buyer self-identifies faster.

And the numbers back this up. 

Bessemer Venture Partners found that vertical (focused) AI companies are growing at 400% annually with 65% gross margins - far higher than traditional SaaS - because they "capture 25-50% of an employee's value" compared to just 1-5% for generic platforms.

Clarity beats capability. 

Every. Single. Time.

🧠 The Method

So how do you find that narrow focus? 

You don't guess.

Remember the example I first mentioned where we discovered our own effort was too broad? We used the existing data to identify the top themes users were already bringing to them. 

Then they built focused experiences around just those topics.

This moves the strategy from opinion to method:

Don't guess what your AI should do. Look at what people already ask it for.

1. Look at the actual conversations users are having now.
2. Find the repeated pain points.
3. Pick one wedge.
4. Build the first/next AI experience around that.
5. Expand only after that wedge is working.

AI feels impressive when it understands the problem they're experiencing right now.

That is what creates demand.

That is what enhances retention.

And that is what makes your AI feel like a product instead of a science project.

👉 Ask yourself these, even if you're not in tech...

• What problem does your business solve so clearly that the right person instantly says: "That is for me"?

• If your AI (or your core service) had to win with just one specific use case, what would it be?

• Before you broaden your offer, ask: what is the single most valuable job this can own?

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✅ Try This, This Week

If you want to see what "narrow and focused" looks like in practice, start with your own brand voice.

Still prompting AI with something vague like "write this in a professional but fun tone"?

THAT IS BROAD.

And the output is usually generic.

The fix is a specific system.

The very first skill inside the Creator AI Skills Stack is called Voice Builder. 

It only takes 30 minutes and maps your exact brand voice architecture - your tone, your language patterns, your audience, your style. 

Once it is installed in Claude, your AI stops sounding like a chatbot and starts sounding like you. 🫵

A specific tool…
For a specific problem. 
Solved permanently. 

That is the whole thesis of this newsletter, applied to your own content.

If you haven't grabbed the Skills Stack yet, you can get it here for $47 🔗 - that is the founder price for the first 500 takers.

P.S. I've been thinking about offering a VERY limited amount of business audits. Think your business meets my AI brain so I can help you see the opportunities in front of you for a fraction of what I charge for a full VIP day. Interested? Message TELL ME MORE and I'll run the idea by you before I announce it.