Recently, a growing number of impressive cases have demonstrated how AI tools can be used for creation. For instance, Replit was used to build a bookkeeping app; Runway generated a short animated advertisement; and ChatGPT was utilized to design a complete webpage.
These examples prompt us to rethink an important question—if AI can not only instantly access global knowledge but produce content and even simulate human thought processes, what capabilities matter the most in the AI era?
I believe that in the future, what will truly set someone apart won’t depend on how much they learn, but rather on their ability to learn deeply, flexibly adapt their knowledge, and proactively pursue learning—in other words, those who excel at Deep Learning and Self-Learning.
Deep learning refers to the ability to organize and understand the information one receives and apply it flexibly in different contexts, rather than simply memorizing or copying it. Self-learning is about the ability to actively explore a problem of interest and identify solutions when encountering an obstacle.
With AI tools, people who possess these two abilities can accomplish tasks that used to take a lot of time with greater speed and accuracy.
Taking entrepreneurship as an example, many entrepreneurs don’t lack good ideas but get stuck at the stage where they wonder whether the market really needs their product. In the past, this meant they had to spend a lot of time doing market research. Now, as long as they know how to ask the right questions, AI can help inventory competitors, organize demand, and simulate scenarios. It’s essentially like having an experienced product manager on hand, giving their ideas a better chance of coming to fruition.
Or consider how, in the past, creating a product was a very difficult task for one person, who needed to learn design, front-end and back-end development, UI/UX, and other skills entirely on their own. Just getting from 0 to 1 was a long and arduous process. But with the help of AI tools, both the barriers to self-learning and the time cost have been significantly reduced. In many cases, it’s no longer necessary to become an expert in a specific field; instead, you can learn and improve as you go along.
A few of the AI tools that have been getting a lot of attention in recent months perfectly illustrate this trend. For instance, Replit, mentioned earlier, allows users to automatically generate and deploy code simply by inputting a single sentence (e.g., “I’m going to develop a chatbot”). This has triggered a wave of “vibe coding” in the tech world, where users simply describe their goals and requirements in natural language, and AI automatically writes the code.
Such tools have not only changed the speed of our creation but also transformed how we learn—instead of needing to acquire knowledge first, we can now understand through “hands-on” practice, making adjustments as we go. That is, rather than needing to spend time learning before creating, learning and creation happen simultaneously.
The same principle can be applied to entrepreneurship. The process of starting a business can generally be broken down into three stages: having an idea, creating a product, and eventually bringing it to market. Previously, each of these three stages required a division of labor across different areas of expertise—but now, AI tools are bringing them closer together.
Returning to our earlier point, AI helps us deal with a lot of knowledge and skills that used to take time to accumulate. As a result, being able to remember the most information or memorize it the fastest is no longer as important. What matters now is the ability to digest and understand what we’ve learned, allowing us to identify and define the right problems, propose solutions, and effectively use tools to turn our ideas into reality.
Deep learning and self-learning are two essential abilities throughout this process. It’s not just about keeping up with AI—it’s also about giving us the opportunity to become true creators of value in a rapidly changing era.
