You're Thinking About AI All Wrong

Everyone is racing to build the biggest AI. Here's why the smarter move is to go smaller.

Welcome, AI Strategists

💫 Current thoughts: Let's be honest, the AI hype is a lot. But what if the race to build bigger AI is the wrong one for your business?

This week's article is about a quieter, smarter approach: the "Small AI" strategy. It’s all about using focused AI experts that solve one problem perfectly—it's the exact strategy I used to build my own AI Chief of Staff.

You'll learn why this is the key to fixing the biggest AI headaches—cost, security, and quality—and how to find your first project today.

This Week's Breakdown

Weekly Blog

AI News Roundup for SMB Decision-Makers and Marketing Professionals

Prompt of the Week:

The first step in a "Small AI" strategy isn't technical; it's strategic. This prompt helps you use a general-purpose AI to analyze your own business and identify the most valuable problem to solve with a specialized expert.

"You are my strategic business advisor. I want to identify the best opportunity to apply a 'Small AI'—a specialized, expert AI model—to my business. Analyze the following information I provide and help me answer three questions: The 'Annoyance Audit,' the 'Data Risk Question,' and the 'Superpower Test.'

[Describe your business here. What do you sell? Who are your customers? What does a typical week look like?]

Now, based on my business context, walk me through these three questions one by one:

1- The Annoyance Audit: Based on my description, what is likely the single most repetitive, low-value, and time-consuming task I do every week?

2 - The Data Risk Question: What is the most sensitive type of information I handle (e.g., client lists, financial data, strategic plans) that I should never upload to a public AI?

3 - The Superpower Test: What is a unique skill or process I have that, if it could be perfectly replicated in an AI, would provide the most value to my business?"

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