Original · Unique Research · 2025-11-09
Editorial note: This historical article reports more than 60,000 X followers in its narrative, while Q5 refers to growth to 30,000. The original does not explain the difference; both figures are preserved. The source includes Q6 and Q10 without answers, and none have been added. “100% empowerment” is the source’s qualitative wording, not an independently verified productivity measurement. Names and account titles without established English forms are conservatively transliterated or translated. Claims and tool choices reflect the original November 2025 account, not current independently verified findings.
If large models ignited a new wave of AI, then people like Qiao Xiangyang are the ones who have truly carried that flame into ordinary people’s lives.
He gives himself three labels: rock music enthusiast, former AI product manager in ByteDance’s commercialization business, and AI content creator. They may seem unrelated, but they correspond perfectly to three dimensions: his temperament, the methodological foundation of his work, and the channels through which he speaks to the outside world. Put them together and you see a species characteristic of the AI era: someone practicing on the front line while continually explaining in public what is happening to the world.
The path he has taken offers a remarkably clear frame of reference for anyone who wants to become an AI creator, operate an AI media brand, or build a “one-person company.”
I. A Second Career That Began with “Astonishment”
Many stories begin with a product launch. Qiao Xiangyang’s turning point came from opening a webpage himself.
In 2022, ChatGPT 3.5 burst onto the scene. He opened the page, typed in a question, and after several rounds of conversation, just one feeling remained: utter astonishment.
He was not astonished merely because the tool was useful; he was astonished because his career would have to be rewritten. After years of working on internet and commercialization products, he immediately realized that this thing would change not only the search bar, but everyone who works with information.
After the initial shock, he did not choose to “wait and see.” He did three very simple things: studied voraciously, evaluated seriously, and shared continuously.
He and several colleagues began tracking every move by OpenAI researchers on X, refreshing papers, demos, and discussions as eagerly as fans waiting for the next episode of a show. When he saw an interesting idea, he wrote down his judgment and recommended tools along the way. He created wave after wave of discussion groups on WeChat and shared a great deal of practical AI experience inside ByteDance. He even held weekly livestreams about AI on the Fingerfly WeChat Channels account, inviting all kinds of friends to join the conversation.
Interestingly, most of the people who casually chatted about AI with him on those livestreams have since become household names in China’s AI content-creator community—Guizang, Hanqing, Orange.ai, AJ, and others. A wave was carrying all of them forward, and his role was to help it spread faster through their circles.
His X account grew from fewer than 100 followers to more than 60,000. This was not the accidental result of a single viral post, but the outcome of a simple logic: in an era when everyone is confused, those willing to dive in first, explore seriously, and explain clearly what they learn will be seen.
Source-image transcription: The historical X profile screenshot shows the display name “Xiangyang Qiaomu,” handle @vista8, website qiaomu.ai, and the bio “A product manager who likes rock music and fishing.” It lists Technology, Beijing, a June 2007 join date, 1,366 following, and approximately 66,000 followers, with a blue verification badge. These are details in the original image, not current account statistics.
II. In an Age of Information Overload, the Scarcest Resource Is a Filter
What truly made him stand out among AI creators was a document that looked decidedly unremarkable.
It was one of the first Feishu knowledge bases he compiled, with entries cataloging AI tools, AI leaders worth following, and recommended key papers. To him, it was simply a memo supporting his systematic learning. To outsiders, however, it was the first attempt they had seen to turn the chaotic world of AI into an intelligible map.
https://xiangyangqiaomu.feishu.cn/wiki/SQ13wrQYai3t5Rk30XjchG7inMg
After Juzi, Baoyu, tw93, and others shared the document, it spread quickly and brought him his first concentrated influx of attention. That moment revealed a reality: in AI, the scarce resource is not news itself, but curators with judgment.
He really made just one crucial decision correctly: when positive feedback arrived, he did not stop. Instead, he treated continuous sharing as a serious discipline.
For him, X is not merely a place to speak; it is his own Feynman learning laboratory. Whenever he learns something new, he tries to explain it in the simplest possible language. Whenever he sees a new model, he forces himself to articulate what it does well and who should use it. Whenever he summarizes a set of tools, he repeatedly refines the structure so others can follow his path and begin using them immediately.
When a friend told him, “You should start a WeChat Official Account; it will have greater commercial value,” he made a second good decision and broadened the formats through which he published.
Thus, “Xiangyang Qiaomu Recommends” began posting prompt templates he had tested, tool recommendations, and model reviews. Short videos, livestreams, long-form articles, illustrated posts—he tried virtually every public form of expression available to one person. The result was straightforward: his reputation accumulated bit by bit, and paid brand collaborations naturally became more frequent.
In an era with too many AI products to keep up with, major technology companies and funded startups alike began to need a particular kind of person: someone who understands products and content, has a stable audience, and can use their own language to translate technical features into felt value.
Qiao Xiangyang happened to emerge at exactly that intersection.
III. AI Is Not a Toolbox, but His Second Nervous System
Had he stopped at reviewing products knowledgeably, he would have been, at most, a highly professional key opinion leader (KOL). What truly turned him into a “super individual” was his own AI-driven workflow.
Many people see AI programming as prohibitively difficult: if you do not understand code, perhaps all you can do is write prompts. His answer is simple: He describes AI programming as providing “100% empowerment.”
Projects he could never have developed before are now within reach, and with models and tools supporting him, he has already completed more than ten. One way to understand this is that he turned “I cannot code” into “I can code with AI.” For someone with a product background, this is not merely an efficiency gain but a reconstruction of professional boundaries: you are no longer just the person who specifies requirements; you can bring an idea to life yourself.
At the information layer, he also treats AI as a second nervous system. Deep search, automated synthesis, and structured summaries compress research that once took several days into a few hours while improving its quality. AI is no longer a search bar for “looking something up,” but a research partner that can start from a question and interrogate it layer by layer alongside you.
His choice of tools is highly AI-native:
For everyday communication, he uses Raycast AI for frequent dialogue and real-time thinking.
When learning something new, NotebookLM and Gemini help him work through YouTube videos and papers, breaking complex material into structured knowledge.
When he needs to turn an idea into a product, he uses tools such as Augment for collaborative programming.
Even for entertainment and inspiration, he experiments with generative tools such as Jimeng, Sora, and Suno, watching how machines “misread” human creativity and extracting new ideas from those misreadings.
AI’s role in his life is no longer a plug-in efficiency boost. It is more like a permanently worn exoskeleton: work, learning, expression, and entertainment have all been rewritten.
IV. A Super Individual Does Not Mean One Person Doing Everything
When people discuss the “one-person company” or the “super individual,” they often romanticize it unconsciously, as though the ultimate form were one person at a computer using AI to look after children, write code, publish articles, negotiate contracts, and handle customer service.
Qiao Xiangyang’s choice corrects that misunderstanding.
His model includes a partner, and together they explore AI education and AI marketing. Their capabilities complement one another, and their thinking continually sparks new ideas in the other. Large models reduce the amount of manual labor, but endeavors that require judgment and long-term commitment remain, in essence, multiplayer games.
The phrase “go farther” has taken on a new meaning in the context of AI:
It does not mean sacrificing your life and filling every available hour.
It means using AI to strip away repetitive labor and employing a small team to build a reliable machine for producing results.
The AI-era super individual is not one person replacing a team, but AI plus a small team replacing the cumbersome large organizations of the past. It is not one person doing the work of ten, but one person using AI to orchestrate ten different kinds of resources so they operate automatically within a system that person designed.
V. The Monetization Logic: From Explaining Tools to Selling Judgment
Once you have an AI-driven workflow and an audience willing to listen, the next unavoidable question is: how do you commercialize it?
Qiao Xiangyang’s main monetization models today are advertising partnerships and consulting services. On the surface, these are two common routes for independent media. In AI, however, their essence is subtly different: you are not selling exposure, but filtering.
For brands and entrepreneurs, an ordinary advertising slot is far less valuable than a clear, credible review. A templated consulting report likewise cannot match the directional judgment of someone who truly understands products, users, and AI trends.
One enormous change brought by AI is that producing content is becoming cheaper at scale while “trustworthy judgment” is becoming more expensive.
A true super individual really sells only two things:
First, the ability to produce reliably and consistently.
Second, the cognitive frameworks and trust accumulated behind that output.
AI can partly amplify the former. The latter can only be earned through long-term practice, mistakes, and self-iteration.
VI. AI’s Ultimate Leverage for Individuals: Not 10x Efficiency, but “One More Possible Life Path”
His experience of AI’s leverage can probably be summarized in one sentence:
AI changed him from someone who could only watch others build into someone who could build for himself.
It enabled work that once took days to become clear to take shape within a few hours.
It extended the boundaries of a product professional beyond PRDs, prototypes, and reports to code repositories, traffic entry points, and business opportunities themselves.
That is certainly an efficiency gain, but it is much more than simply being a little faster. What it truly changes is the set of viable paths through your life.
People who cannot code can use AI programming to try product experiments.
People without a team can use AI and a few partners to assemble a lean combination of “one-person company plus a group of models.”
People without resources can attract major technology companies, startups, and partners through sustained publishing.
AI redefines individual value not by turning you into a more obedient cog, but by giving you a complete toolkit for building your own machine.
VII. A Piece of Advice for Those Who Follow: Start by Asking Better Questions
For those who also want to become AI creators, operate AI media brands, or build “one-person companies,” Qiao Xiangyang’s advice does not begin with which programming language to learn or how many accounts to open. It starts at a deeper level: changing your way of thinking matters more.
The core is learning to ask AI questions.
If you are curious about a field, break that curiosity into a series of questions, give them to different models, and keep probing, comparing, and correcting.
If you want to learn a new skill, ask AI to break down the learning path, simulate a teacher, and assign exercises.
If you are preparing a project, have AI interrogate you from four angles: users, technology, business, and competitors.
At the tool level, he believes individuals should make their biggest bets on just two categories:
Using AI to write code and using AI for deep search.
The former determines whether you can build and test your ideas yourself.
The latter determines whether you can quickly find a relatively reliable cognitive anchor in a highly uncertain world.
You can take your time experimenting with and changing the remaining tools. But once you master these two things, you already possess the minimum foundation for evolving independently amid the AI wave.
When we talk about “Pioneering Intelligence | The Age of the Individual,” it is easy to focus on spectacular models and the product launches of technology giants. Qiao Xiangyang’s story reminds us, however, that the choices that truly rewrite an era often look very “small”:
That first experience that astonished him enough to keep exploring for several more hours.
That knowledge document he initially compiled only for his own learning.
Those long articles and reviews that were tiring to write, yet which he persisted in publishing one after another.
The tide of an era is always immense, but an individual’s transformation often begins with a very small action.
If you are interested in AI but still do not know where to begin, consider doing one thing today:
Choose a question you genuinely care about, open a model you find convenient, formulate the question clearly, pursue it to the end, and then share your understanding with at least one other person.
In this world, everyone willing to ask and answer questions seriously is an early form of some future “super individual.”
Selected Interview Q&A
Q1: If you had to introduce yourself with three labels, which would you choose?
Qiao Xiangyang: Rock music enthusiast, former AI product manager in ByteDance’s commercialization business, and AI content creator.
Q2: How did you fall down the AI rabbit hole?
Qiao Xiangyang: I first used ChatGPT 3.5 in 2022 and was profoundly shaken. At that moment, I felt my career might have to start over.
Q3: What was your first reaction after that?
Qiao Xiangyang: I voraciously followed OpenAI researchers and all kinds of AI news, learning while commenting and recommending tools on X. At the same time, I created many WeChat groups for discussion and shared my experience widely inside ByteDance.
Q4: What first helped you break out in the AI community?
Qiao Xiangyang: A Feishu knowledge base I compiled for myself, containing AI tools, AI leaders, and recommended papers. After Juzi, Baoyu, tw93, and others shared it, my following surged.
Q5: How did your X account grow from fewer than 100 followers to 30,000?
Qiao Xiangyang: It was simple—just two things: sharing frequently and genuinely testing and explaining what I used. I treated X as my own Feynman learning laboratory and kept doing it for a long time.
Q6: Why did you later start publishing on a WeChat Official Account as well?
Q7: Are you working alone now, or do you have a team?
Qiao Xiangyang: I have a partner and a small team. We explore AI education and AI marketing together. Our abilities complement each other, and we spark ideas in one another; it is more stable and enables us to go farther than working alone.
Q8: In one sentence, how would you describe AI’s role in your work?
Qiao Xiangyang: Projects I could not handle before can now be completed with AI programming. Research that once took days can now be done in a few hours, and the result is more systematic.
Q9: Which AI tools do you use most often?
Qiao Xiangyang: I use Raycast AI for everyday conversations, NotebookLM and Gemini primarily for learning, Augment for programming, and Jimeng, Sora, and Suno for inspiration and entertainment.
Q10: How do you currently monetize your work as a “super individual”?
Q11: What is the greatest leverage AI has given you?
Qiao Xiangyang: It took me from not knowing how to code and processing information slowly to being able to build projects myself and understand a field quickly.
Q12: What is your one piece of advice for people who want to become AI creators or build one-person companies?
Qiao Xiangyang: Stop overthinking and start asking AI questions voraciously right now. Prioritize two things: learn to use AI for programming, and learn to use AI for deep search. You can fill in everything else gradually.