Let me let you in on a little secret. In all my time consulting with folks building AI apps and assistants, I've noticed something fascinating. Want to know how I solve about 90% of the problems that come my way? With one simple question:

"What is the scope?"

That's it. Four words.

More often than not, when people come to me with their AI projects in shambles, it's because they've tried to boil the ocean. They're building the AI equivalent of a Swiss Army knife when all they really need is one really sharp blade.

We’re going to avoid this mistake by starting out with simplicity in mind.

Here’s the podcast version

Let’s get started

Razor Sharp

Here's the thing: AI is powerful. Real powerful. It can do an awful lot. And it's tempting to want to do it all. After all, these models are incredibly powerful, right? Surely we should leverage them to solve ALL THE PROBLEMS!

But here's a little secret I've learned the hard way: the most successful AI apps aren't the ones that do everything. They're the ones that do one thing exceptionally well.

Think about it. When was the last time you used a Swiss Army knife to do anything other than open a bottle? Exactly.

Now, when was the last time you used a specialised tool that made a specific task infinitely easier? I bet it was much more recently.

Same for our AI app. We want to focus it all the way down to ONE thing. This is going to help us with both parts of our business: marketing and building.

I’m drawing in part from Peter Thiel's book "Zero to One" here. While Thiel's book covers a lot of ground, there's one idea that's particularly relevant to us: the power of monopoly through specialization.

Thiel argues that the most successful companies don't try to compete in crowded markets. Instead, they create their own markets by doing one thing so well that they essentially have no competition. In the context of AI apps, this doesn't mean you need to invent a new form of artificial intelligence. It means finding a specific, underserved niche and solving their problem better than anyone else could even dream of.

Think about it like this: would you rather be a small fish in a big pond, or the only fish in a small pond that you've made uniquely yours?

Why Focused AI Apps Work So Well

Now, let's dive into why this laser-focused approach works so brilliantly for AI apps specifically.

Mastering the Learning Curve

When you're focused on solving one specific problem, it's easier to train your AI model effectively. You're not trying to boil the ocean; you're just trying to make the perfect cup of tea. This focused approach allows you to really dive deep into the nuances of your specific problem domain.

For example, let's say you're building an AI app to help copywriters generate headlines. By focusing solely on headline generation, you can train your model on thousands of successful headlines, understand the subtle differences between headlines for different industries, and even account for trends in headline effectiveness over time. This level of specialisation is simply not possible if you're trying to build a general-purpose writing tool.

The Marketing Magic of Simplicity

"So, what does your app do?"

If you can't answer this question in one simple sentence, you're in trouble.

One of the beautiful things about a highly focused AI app is that it's incredibly easy to explain - and sell.

Imagine you're at a networking event. In one corner, there's someone talking about their "AI-powered productivity suite with 57 features to revolutionise your workflow." (Swiss Army Knife). In the other corner, there's you, saying, "My AI app writes email subject lines that double open rates."

Who do you think is going to get more interested leads?

When your app does one thing exceptionally well, your marketing message becomes crystal clear. You're not selling features; you're selling a specific, tangible outcome. And that's waaaaay easier for potential customers to grok and want to buy.

The Pricing Sweet Spot

Here's a counterintuitive truth: specialized tools often command higher prices than general-purpose tools. Why? Because when you solve a specific problem really well, you become indispensable.

Let's go back to our headline-generating AI. If you're a copywriter or a marketing agency, how much would you pay for a tool that consistently helps you write headlines that perform 50% better than what you could come up with on your own? Probably quite a bit, right?

Now, how much would you pay for a general "AI writing tool" that does a so-so job at everything from headlines to blog posts to product descriptions? Probably not as much. And right now the AI market is flooded with this sort of “suite”.

Becoming the Big Fish

When you try to build an AI app that does everything, you're competing with tech giants (Microsoft) and well-funded startups (ie. Jasper). It's an uphill battle from day one.

But when you narrow your focus to a specific niche, suddenly the playing field changes. You're no longer competing with other AI tools. Instead, you're competing with the old, manual ways of doing things in your chosen niche. Massive, hard to overestimate, difference. Hell, this is probably the most important takeaway this week.

By solving a specific problem really well, you can quickly establish yourself as the go-to solution in your niche. You become the expert, the specialist, the one that everyone in that niche recommends to each other.

And here's the kicker: once you've dominated one niche, you can expand to related niches. You're not stuck in your small pond forever. But by starting focused, you give yourself the best chance of success right out of the gate. Capiche?

Narrowing Down Your Idea

So, how do we take the ideas we generated in Part 1 and refine them into laser-focused tools? Let's use an AI prompt to help us out. Use this below our work from before:

You are an AI specialising in product development and market analysis. Based on my AI app idea, help me refine it into a highly specific tool with one primary input and output. Then, analyse the refined idea for marketability and complexity.

Please provide:
1. A refined, highly specific version of the tool
2. The primary input and output
3. A brief user experience flow
4. A simple backend process flow
5. Analysis of marketability (scale of 1-10, with reasoning)
6. Analysis of complexity (scale of 1-10, with reasoning)

If multiple ideas are presented run this process for each idea.

Run this prompt for each of your top ideas from Part 1. You can run all the ideas at the same time but ideally one at a time (so the AI can focus on ONE idea - there’s that focus again). The goal is to distill each idea down to its essence - the one thing it can do better than anything else out there.

Once you've run the prompt for your top ideas, it's time to analyse the results. Remember, we're looking for high marketability and low complexity. This combination gives us the best chance of creating a successful AI app quickly.

Look for ideas that score 7 or higher on marketability and 5 or lower on complexity. These are your golden tickets - ideas that solve a real problem (high marketability) but won't require years of development (low complexity).

If none of your ideas hit this sweet spot, don't worry! S’all good.

Go back to the drawing board, generate a few more ideas using the prompt from Part 1, and run them through this refinement process. Remember, this is all about iteration and learning. And it’s much better to chop and change ideas at this stage before we start building.

What's Next?

In Part 3, we're going to take your refined idea and put it to the test in the real world. We'll explore validation strategies to ensure there's a real market for your AI app before you invest time and resources into building it.

Keep Prompting,

Kyle