Original · Unique Research · 2025-11-07
Editor’s note: This complete English edition preserves the original report’s commentary and Hei Qiang’s interview statements as of November 7, 2025. Chaohui AI and Hei Qiang are romanizations of the Chinese names, not independently verified official English names. The source does not specify the currency of the funding figure or identify the LinkedIn report quoted by the interviewee. Funding, production-duration and creator-budget claims remain source-attributed rather than independently audited findings. ‘This year’ refers to 2025. In this article, personal IP refers to a personal brand. No publication location is inferred.
If this era has an invisible production line, it is probably the stretch between being surfaced in someone’s feed and being trusted.
Short-form video, livestreaming, and in-feed advertising assault our attention day and night. Platform algorithms are like conveyor belts that never shut down, constantly placing piece after piece of content before users’ eyes. For many companies, simply appearing in the feed seems to put them at the threshold of a sale. Reality is harsher: being seen does not mean being paid; exposure does not mean business.
Hei Qiang founded Chaohui AI precisely at the break in that production line.
He has spent 14 years fighting on the front lines of content marketing and has watched too many traffic myths rise to a peak and then collapse. Algorithms change and audiences migrate between platforms; every time a period of easy growth ends, someone fails to get out in time. Eventually, he recognized a brutal but simple fact: platforms control how traffic is allocated, but they cannot control how trust is allocated. Companies that rely solely on rented traffic will ultimately be dragged under. What can truly save them is a foundation of trust they own.
What Chaohui AI wants to do is help companies reinforce that foundation and use content to build a storehouse of trust in customers’ minds.
I. From Competing for Traffic to Building Trust
Under the traditional traffic model, customer acquisition is a company’s central task: find channels, buy traffic, place ads, and compete for a sliver of exposure under the platform’s rules. Hei Qiang takes a somewhat contrarian view: instead of renting traffic indefinitely, companies should learn to create customers themselves.
“Creating customers” does not mean conjuring demand from thin air. It means using content to accumulate enough familiarity, understanding, and trust before customers ever encounter you. When they finally see you in their feed, the unspoken thought is no longer, “Who is this?” but, “Ah, I know him.”
That is why Chaohui AI sums up its positioning in a vivid line: put a human face on content, make your value worth more, and make business easier to win.
Putting a face on content is not merely about having a real person appear on camera. It means organizing the content universe around people. The boss is not just a signatory hidden behind a corporate LOGO, but a living person with stories, emotions, and a point of view. Employees are not cold ID badges, but individual content nodes with professional identities and the texture of real life. External KOCs are not merely ad inventory, either; they extend a chain of mutual trust.
When content is anchored in people, it ceases to be mere marketing collateral and becomes trust capital that compounds over time. Every appearance quietly reinforces the same message: this company is worth talking to.
II. Every Company Is an MCN
Traditional MCNs operate individual influencers as product lines. Chaohui AI wants each company itself to become an influencer MCN.
In its vision, a company has at least three tiers of content creators:
The boss is the KOB (Key Opinion Boss), representing the company’s values, sense of direction, and ultimate decisions. Employees are KOSs (Key Opinion Staff), providing professional perspectives, execution insights, and everyday touchpoints. External creators are KOCs, standing on the user’s side and extending trust outward through advocacy and product recommendations.
The content-MCN operating platform Chaohui AI is building connects all three roles: people at one end, content at another, and business at the third. Bosses no longer need to agonize over every short video or be held hostage by filming schedules. With the company’s AI BOSS product, one filming session can generate a continuous stream of short-form content for the year ahead. That session captures expressions, tone, speaking style, and values all at once; AI and the underlying content-engineering system handle the truly labor-intensive production work.
At the other end, its AI-powered creator-seeding business redesigns the way companies find creators. In the past, each creator had to be approached and contracted individually. Now, companies can use one-tenth of a traditional budget to mobilize ten times as many creators to speak for them. AI supports matching, generation, adaptation, and coordination, while people remain responsible for strategic selection and relationship management. An individual can even use these capabilities to build a business as an AI-enabled creator-marketing intermediary.
There is a clear judgment behind this: AI is not about saving the salaries of one or two copywriters. It is about giving a small team the productive capacity that once required a large MCN—and turning the once-expensive resource of content capability into infrastructure that can be replicated and scaled.
III. Human Expertise + Intelligence: Deliver Results Before Selling Tools
Many AI companies begin by following the software-sales playbook: build a SaaS product, define a set of features, and design a pricing model. The problem is that most companies do not actually want a tool. They want lower customer-acquisition costs, steadier conversion, and more predictable growth.
Hei Qiang is candid about this: today’s artificial-intelligence technology is remarkable, but understanding how to apply it in business remains at an early stage. Simply packaging algorithms as a product is not enough. Chaohui AI therefore chose the harder path—sell results first, then talk about tools.
Selling results means first standing on the customer’s side and working through a combination of human expertise + intelligence: people provide experience and judgment, while AI handles production and amplification. When serving clients, for example, the team acts not merely as a software vendor but more like a strategist for content operations: it works with clients to unpack business scenarios, refine the content cadence, monitor data, and conduct reviews. AI, digital humans, video generation, SORA2, and other technologies are engines embedded in this process, not exhibits placed on display at the front of the shop.
Seen from this perspective, Agentic AI—agents capable of proactively perceiving, planning, and executing—is not simply a fashionable new concept, but a natural extension of the organizations of the future. Hei Qiang paints a vivid picture: companies will have countless AI employees, while the truly scarce people will be the small number of “AI-employee summoners” who can deploy and direct them and set their goals and boundaries.
In other words, the central organizational question will no longer be whether there are enough hands, but whether there are enough summoners. For the small, high-performing teams of the future, the decisive advantage may not be headcount but the number of AI counterparts each person can bring into action.
IV. Taking Content and Trust Abroad: Learning to Adapt Is Mandatory
Content and trust are both, at heart, cultural products. The moment they leave their home market, every expression, joke, and emotional cue that once seemed self-evident must be realigned.
This year, with an introduction from Unique Capital, Chaohui AI chose Vietnam for an initial overseas trial. It is a market of immense potential but also deep complexity and diversity: a young population, high social-media penetration, and a rapidly growing e-commerce ecosystem make it look much like China during an earlier window of opportunity. Yet moving an entire content-MCN operating methodology there reveals countless subtle mismatches. The language system, social etiquette, acceptance of bosses appearing on camera, and the logic of local platform ecosystems all force an apparently mature solution to be taken apart and reworked.
Hei Qiang does not shy away from these problems. His judgment is direct: going global is unavoidable, but going global is not copy and paste. For Chaohui AI, it is a journey of self-evolution. Only through friction with different cultures can the company distill which principles are universal in the content era and which elements must be rebuilt locally.
At a broader level, this also reflects a trend: the tools with real staying power will no longer be tactical products that serve a single market. They will be long-term assets that cross languages and cultures and help companies build systems of trust in different environments.
V. The Age of the Individual: When Everyone Steps in Front of the Camera
The theme of our conference is “Pioneering Intelligence | The Age of the Individual.” It may sound like an elegant slogan, but Hei Qiang interprets it through a very concrete fact: one-person companies already exist in the real world.
In the traditional industrial era, production was highly centralized and capital-intensive; without an organization, a factory, and a team, it was difficult to speak of a company. Today, however, generative AI has sharply reduced the cost of producing and distributing content and delivering some services. One person can have countless AI employees: some help write, some film, some edit, some handle customer service, and others work on spreadsheets and analysis.
Of course, the emergence of one-person companies does not mean everyone should quit their job without another job lined up and become a digital nomad. The real change is that an individual’s content capability is becoming a new form of literacy. Individuals and teams that cannot write or film, are afraid to appear on camera, or are unwilling to express themselves will find it increasingly difficult to establish a clear presence in the business world.
Every opportunity has a challenge on its other side. Generative AI has indeed lowered the barrier, enabling people with limited writing or editing skills to make reasonably good content. Yet precisely because there are few secrets left in the world, the vast majority of merely similar content will quickly disappear into an ocean of supply. The real threshold is shifting to other dimensions: How deeply do you understand users? Can you develop a distinctive methodology? Can you explain complex issues clearly enough for a layperson to understand? Can you keep producing over the long term, giving trust time to grow?
In Hei Qiang’s view, therein lie both the greatest opportunity and the toughest challenge in this field. The opportunity is an enormous market as virtually every industry becomes content-driven. The challenge is that, although the barrier to entry appears low, invisible distinctions in level and quality are still being redrawn.
VI. TLG: Grow by Teaching Others
In recent years, two acronyms have dominated conversations about growth: PLG (Product-Led Growth) and SLG (Sales-Led Growth). Hei Qiang proposes a concept that looks simple but is, in fact, highly ambitious: TLG, or Training-Led Growth.
For Chaohui AI, this is more than a memorable label. It is a path particularly well suited to content entrepreneurs in the AI era: first, teach the market how you understand a particular problem. As you teach, you establish intellectual authority while also identifying the people who genuinely need your solution. Once they enter your courses, events, or communities, a transaction becomes only a matter of time.
TLG rests on an implicit premise: you must believe deeply enough in the value of knowledge to trust that teaching your method will not weaken your competitive position but strengthen your stock of trust. That is disruptive in industries accustomed to keeping expertise hidden. For individuals and small teams, however, it may be one of the most practical and compounding paths over the next 1-3 years.
You can begin by asking yourself several questions in your own field: Can I use content to explain what I do to someone who knows nothing about it? If I break down my experience from the past five years, can I teach it as a short course that others can actually use? When someone mentions this niche, am I one of the three names that naturally come to mind?
TLG may be less a standardized growth model than a demand you place on yourself: do not wait for the product to be perfect or the team to be large. Start by teaching others, and let yourself be seen, understood, and trusted. Content is the shell; trust is the core; business is what naturally follows from their long-term interaction.
If one sentence could sum up what Hei Qiang and Chaohui AI are doing, it would be this: in an era held tightly in traffic’s grip, they turned around and built a business on trust.
For everyone standing at this historical crossroads, the more important question is not whether AI will replace me. It is this: when content becomes the new infrastructure and trust the new scarce asset, what must I do to become worthy of someone’s trust?
Selected Interview Q&A
Q1: Please introduce yourself and explain what you and Chaohui AI actually do.
Hei Qiang: I am the founder of Chaohui AI. I have spent 14 years building businesses in content marketing, and our team has raised close to 100 million in funding. Chaohui AI’s core proposition can be summed up in one line: “Put a human face on content, make your value worth more, and make business easier to win.” We believe that customers must first encounter you in their feed before you have a chance to win an order. But what actually closes a sale is content that creates trust—and people are the central carriers of that trust.
Q2: Specifically, how do your products help companies create content and acquire customers?
Hei Qiang: We want to help every company build its own “content-MCN operating platform.” The boss builds an IP identity as the KOB; employees form a content matrix as KOSs; and external creators seed recommendations as KOCs. In essence, we turn every company into an influencer MCN that uses an ongoing stream of content to attract traffic and prompt customers to initiate collaboration.
Q3: You have said that “platforms control traffic, but they cannot control trust.” Could you elaborate?
Hei Qiang: In the new-media era, companies seeking customers must first “rent traffic” or “buy traffic” from platforms. Yet traffic costs keep rising, leaving companies’ lifelines in the platforms’ hands. We eventually identified one crucial point: platforms control “who gets surfaced in a feed,” but they do not decide “whom customers trust.” LinkedIn has also emphasized in a report that “trust wins business.” Chaohui AI’s original purpose, therefore, is to help clients build a foundation of trust-based content.
Q4: How do you view the current breakthroughs in generative AI, and which frontier technologies are you using?
Hei Qiang: The greatest breakthrough in generative AI is its ability to “create something from nothing”—to turn imagination directly into content. For the content industry, this is a nuclear-scale change. We have already integrated digital-human technology, SORA2, and other capabilities into our products, allowing a boss or team to film once and then produce content at scale for a long time.
Q5: With technology advancing so competitively, how do you balance “innovation” and “implementation”?
Hei Qiang: AI technology is very hot right now, but, frankly, the whole industry’s understanding of “business” is still at an early stage. Technology alone is not enough. We chose the “human expertise + intelligence” path: instead of merely selling software, we prioritize delivering visible “results” to clients. Human experience + AI capabilities are more dependable and do more to help companies genuinely improve their business.
Q6: How do you think new concepts such as Agentic AI and AI employees will affect organizations?
Hei Qiang: I strongly believe in one trend: companies will have countless AI employees but only a small number of “AI-employee summoners.” Future organizations will be smaller and more focused. One person will be able to direct many digital AI employees at once, profoundly disrupting traditional organizational structures.
Q7: Have you already begun expanding overseas? What have you learned from your trial in Vietnam?
Hei Qiang: With an introduction from Unique Capital, we began testing the implementation of our solution in Vietnam this year. Frankly, every aspect is still being worked out, and there will inevitably be local mismatches. But I believe global expansion is an unavoidable path. We will continue exploring overseas and find approaches better suited to each local market.
Q8: How do you understand “Pioneering Intelligence | The Age of the Individual”?
Hei Qiang: To me, this is not a concept but reality: the “one-person company” has already arrived. One person can have N AI employees working on their behalf. Especially in industries seeing dense waves of new technologies and business models, one-person companies and digital nomads are likely to become the norm.
Q9: Can you give a concrete example of how Chaohui AI empowers individuals and small teams?
Hei Qiang: Take our “AI BOSS” business. A boss needs to film only once, and the content can be used for a year, greatly reducing the time and production costs required for IP-driven short videos. Or take our AI creator-seeding business: with only one-tenth of the former budget, a client can mobilize ten times as many creators to publish content. An individual can also use this model to launch and run a business single-handedly.
Q10: From the perspective of your field, what are the biggest opportunity and challenge right now?
Hei Qiang: The greatest opportunity is that the market is large enough: business has entered the “content era,” and companies without content capabilities will inevitably be eliminated. The greatest challenge is that the barrier appears low: generative AI has removed most of the world’s secrets and democratized technology, so we must keep iterating our products and methods to build real barriers of our own.
Q11: What advice would you give individuals and small teams for the next 1-3 years?
Hei Qiang: People often talk about PLG and SLG. I prefer TLG—Training-Led Growth. Grow by teaching: use training, sharing, and the publication of your methodology to build trust and win customers at the same time. This “teach instead of sell” model is an excellent fit for Chaohui AI, as well as for many entrepreneurs and content-focused individuals in the AI field.