Why is other people's ChatGPT better?

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ChatGPT is often criticized for being incomprehensible. The webmaster of Computer Toys, Huang Zhongyi (Esor), has mastered generative AI to such an extent that articles generated by ChatGPT can be put online with only slight modifications. How does he do it?

"I am used to having three things running in my head that require creative thinking at any time," said Esor Huang, editor-in-chief of City Publishing and blogger of Computer Toys, who writes various articles on improving digital productivity. "My brain is exploding" is his daily routine.

Looking at Huang Zhongyi's to-do list, the tasks of his blogging side job include updating an article of about 10,000 words every three days on average, producing e-newsletters, managing YouTube, and writing Facebook posts. The work of a full-time editor requires meeting with authors, writing promotional plans, and producing marketing materials. At the same time, he has an elementary school child at home who needs time to accompany him. One can't help but wonder how Huang Zhongyi can have enough brainpower and time to cope with it?

In order to complete all the tasks within the time limit, Huang Zhongyi did not have a clone and relied on the assistance of his ChatGPT colleagues.

For example, Huang Zhongyi uses ChatGPT to reduce the number of lengthy meetings that many workers suffer from. The most important job of a publishing editor is to focus on the book theme and outline with the author. This is a time-consuming brainstorming meeting that often fails to reach a conclusion quickly. To improve this situation, Huang Zhongyi will input past discussion records into ChatGPT and provide the author with original information, such as past course outlines, blog content, etc., and then ask ChatGPT to generate a book outline.

"The author was shocked," Huang Zhongyi said with a smile, because as soon as the author finished speaking, he sent the complete chapter suggestions generated by ChatGPT to the other party, and they could discuss the direction of the book right away. Without the help of AI, it would often be difficult to get into the outline discussion with just a one-time focus meeting.

In addition to improving meeting efficiency, "writing" is his side job. His ability to control generative AI is so high that articles generated by ChatGPT only need slight modifications before they can be put on the shelves, which makes many writers astonished. After applying ChatGPT, Huang Zhongyi can now write an article of about 10,000 words in three hours instead of two or three days.

Why is Huang Zhongyi's ChatGPT more accurate and obedient when using the same generative AI tool? He shares the key to his collaboration with ChatGPT.

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Generate draft: build personal database and provide workflow
Huang Zhongyi emphasized that generative AI is not magic that creates something out of nothing, but a text chain based on data. The ChatGPT model has mastered most of the information on the Internet, but 99.9% of the data does not meet the needs. To make the articles produced by ChatGPT meet the needs, the key lies in how accurate the data provided is.

Huang Zhongyi can be said to be a "process management control" and "record control". His blog is full of experiments with various planning and note-taking structures, which allow Huang Zhongyi to have a large amount of clearly structured data to use. These notes accumulated over more than ten years are his moat that allows him to surpass others.

For example, when he wants to write an article on the topic of "Overcoming Procrastination", his first step is to select notes related to the topic from the note library, import them into ChatGPT, and give clear step-by-step instructions:

"You are a psychology expert on overcoming procrastination. I would like to write an article about how ordinary people can overcome procrastination in their daily lives, starting from the emotional and psychological level. Please analyze the file I uploaded step by step and list the key points in the file paragraph by paragraph."

With native data, ChatGPT can generate an outline and use its most powerful "permutation and combination" skills to write a draft article that fits the topic.

"Using AI is like a supervisor leading people. You need to give your subordinates reference examples, your work methods and goals," Huang Zhongyi reminded that only by giving accurate instructions can the expected output be achieved. Workers can start recording their work content and steps from today and build their own database. Only by understanding their own work can they use AI correctly.

Tutorial article: When your brain gets stuck, debate with ChatGPT
Once you have a draft, directly copying and pasting it may be usable, but it may lack sharp viewpoints and depth of argument. Huang Zhongyi recommends that workers have at least three rounds of dialogue with ChatGPT after reading the AI-generated article to improve the quality of the article.

For example, if he wants to write an article to teach readers "How to write goal notes", after ChatGPT provides the step-by-step framework for writing goal notes, Huang Zhongyi will continue to ask about the details, such as: "We know that we need to break down the goals, but we are not sure whether the small goals we break down are appropriate?" Another trick is to provide your own arguments and ask ChatGPT if there are any loopholes and how to improve them?

Through questions and answers, the originally confused brain can be sorted out and think deeply, making the article more interesting.

In the future, Huang Zhongyi hopes that AI can automatically find suitable files from note-taking software based on the topic, without him having to search manually. More new ways of using generative AI are yet to be tested as he writes articles.



Graphics by Cheers Team
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This article is authorized to be reposted from: Cheers Happy Workers ( original link ), please do not reprint without permission.

【Extended Reading】

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