Summary of the Core Content
This article vividly depicts the “collective lost path” of AI entrepreneurs: from being obsessed with creating technical demos (believing that “once something is made, it’s not far from making money”), to fantasizing about running a “one-person company” where AI handles all aspects of production, sales, and revenue collection, to turning to self-media to attract customers (using traffic to explain why their products don’t sell), and finally ending up as someone who “teaches others how to start an AI business” by selling their own experience. The article exposes several illusions about the commercialization of AI, emphasizing that a real AI business needs to focus on specific customers, solve real problems, and take responsibility for the outcomes, rather than chasing technical showmanship or traffic bubbles.
Detailed Analysis
1. Don’t Be Misled by Technology: A Working Demo Does Not Equal a Profitable Business
AI has made it much easier to develop products—what used to require a team of several months can now be done by one person in just a few days (creating code, building interfaces, and integrating models). However, many people mistakenly assume that just because a product can run does not mean the business will be successful.
For example, you might create an AI writing assistant with a nice interface and all the necessary features, but no one buys it. Why? Because users may already have access to free tools like ChatGPT, or your assistant doesn’t address their specific needs (for instance, if they need help with plagiarism in their research papers, but your assistant only generates content).
Technology solves the question of “whether something can be made,” but business needs to answer “who needs it, why would they buy it, and how much are they willing to pay?” AI cannot help you with these questions. It’s like cooking; just because you can cook doesn’t mean people will pay for your food—your food must taste good, be priced reasonably, and meet the needs of potential customers (for example, if office workers need fast food, but you only serve home-cooked dishes).
2. A “One-Person Company” Is Not a Machine Without People: The Key Is Still Humans
Many people imagine a “one-person company” as one where they sit in front of their computer while dozens of AI agents handle everything automatically—producing products, posting content, handling sales, and collecting payments. But in reality:
- No one will buy your product unless you find customers yourself;
- AI cannot answer all customer questions (for example, corporate clients may ask about data security, which AI cannot address);
- If there are issues with the product, AI won’t take the blame for them (if the generated content violates regulations, you will).
A real one-person company uses AI to save time so you can focus on tasks that AI cannot handle, such as selecting customers, building trust, and taking responsibility. For instance, you might use AI to write copy, but you still need to find an advertising agency, communicate with clients about their needs, and apologize and make corrections when mistakes occur.
3. Self-Media Turns Customer Focus into Self-Promotion: From Selling Products to Selling Your Story
Receiving feedback on products is slow and frustrating: you spend three months developing something only for the client to say they don’t need it; after talking to ten companies, you realize they only want one of your features. However, self-media is different: you can post an article and see readings, likes, and followers in just a few hours—even if there’s no revenue, it feels like progress. Gradually, you start spending more time on creating content. Initially, you use content to promote your product; later, you reduce the time spent on development to focus on content creation, and eventually, the product becomes secondary as you start sharing how you use AI in your business. As a result, you go from selling an AI product to selling your own experiences.
4. Real AI Businesses Are Small and Specific: Solving Real Problems
Many people claim that AI will “empower various industries” and “restructure production processes,” but the truly profitable AI businesses are often very specific:
- Helping factories reduce the time spent on inspecting defective parts;
- Assisting restaurants in optimizing inventory to minimize waste;
- Reducing customer service costs for companies by automating common questions.
These businesses don’t constantly talk about using AI; customers buy the results—whether it’s a factory saving money or a restaurant reducing waste. They won’t pay just because you use AI tools; they will ask, “Can you solve this problem for me? How much does it cost? Who is responsible if something goes wrong?”
5. Be Cautious of the “Gold Rush”: Selling Real Value Is the Long-Term Solution
Some say that during a gold rush, the most profitable businesses are those that sell tools (like shovels). But you need to distinguish between “real tools” and “gold rush illusions”:
- Real tools: For example, selling AI development tools that help people create products faster or training companies on how to use AI for quality control; these provide real value and solve problems for customers.
- Gold rush illusions: Claims like “earn 100,000 per month with AI” or “create an AI system that makes money automatically in three days” are based on unproven promises. The simple test is to ask yourself: What specific benefit will this product bring me? (For example, “saving two hours per day on writing copy” is concrete; “changing my life with AI” is abstract.)
6. In Conclusion
AI makes it easier to create products, but harder to choose the right ones to develop. Real AI entrepreneurship is not about showing off technical skills or chasing traffic; it’s about identifying specific customers, solving real problems, and taking responsibility for the outcomes.
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(Word count: approximately 1500 words)