As the Bubble Fades, Who Dominates Attention in the AI Era? 2026 China-UK AI KOL Influence Atlas
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As the Bubble Fades, Who Dominates Attention in the AI Era? 2026 China-UK AI KOL Influence Atlas
As the entire web plunges into a carnival of involution over model capabilities, a group of "technical translators" are quietly reconstructing the landscape of attention.
Navigating Web3 tides with focused insightsAuthors: Alan, Amelia | Biteye Content Team; Denise | XHunt Operations Team
In the summer of 2026, information feeds on social platforms are refreshing in milliseconds. One second, a large language model releases an update; the next, tens of thousands of "in-depth interpretations" are already everywhere.
An independent developer told us that the first thing he does when he wakes up now is no longer scrolling the timeline, but quickly scanning a few familiar avatars to see what new tricks they Vibe Coding last night.
"I only trust those who have actually done it," he said.
This seemingly paranoid trust points to a truth ignored by most people:
In today's era of rapid advancement in large model technology, general information itself is depreciating at the speed of light.
Traditional tech media accounts that relied on forwarding news flashes, translating overseas announcements, and simply piecing together news have gradually lost users' patience. The true scarce resource is no longer "who said what first," but "who can tell me whether this is reliable and how I should use it."
To uncover the real operating logic of this hidden circle, based on exclusive data and capability models from the social analysis tool @xhunt_ai, we deeply calculated tens of thousands of tweet samples from nearly 400 top AI KOLs in the Chinese and English ecosystems.
We found: Opinion leaders in the AI era are undergoing a profound transformation from "information intermediaries" to "productivity enablers."
1. Core Findings: From Distributing Opinions to Distributing Productivity
In the context of the traditional internet, an individual with a brilliant idea wanting to implement it needed to mobilize a whole complex chain of manpower: backend, frontend, UI, product manager... The long collaboration process was enough to wear away most of the enthusiasm. Today, AI tools have crushingly compressed this production chain. Codex, Claude Code, Cursor, Lovable transform programming barriers into logic and architecture capabilities; Seedance, GPT Image, Kling, Nano Banana directly cut down the complex thresholds of image and video production.
But this triggers a counter-intuitive industry phenomenon: when anyone can rely on AI to batch-produce long-winded articles, high-quality content becomes "cheap" and readily available, making trust scarcer than ever before.
The core value of AI KOLs does not lie in their ability to make AI spit out a piece of fluff faster than ordinary people. It lies in their ability to be the first to use human-machine collaboration to concretize vague AI usage capabilities into results that others can see, run, and directly reuse. This is no longer distributing opinions, but distributing production capabilities.
For example, when a new model claiming to "defeat Claude Opus 4.7" is released, users are already tired of the same old press releases. They are eager to know from trusted KOLs: "Will it hallucinate in real code development? Is this product, which looks so cool in the official polished video, actually an out-of-the-box productivity tool for ordinary people?"
The attention weathervane has reversed: from "what happened," upgraded to "whether it matters," and then to "how to use it."
In a field full of noise, AI KOLs play the role of practical pioneers and trust fulcrums.
2. Who is Playing This Role: Tech Veterans and New Generation Blue Ocean
A relatively common industry bias is: "Most AI KOLs are marketing accounts that quickly gained followers by eating dividends after the ChatGPT explosion at the end of 2022." However, XHunt's account registration generation statistics 用 data falsified this claim: the generational structure of AI KOLs presents an inverted pyramid distribution.
- Dominance of Senior Practitioners: In the English ranking, early users registered between 2007 and 2015 account for up to 62.9%; this proportion also reaches 58% in the Chinese ranking. This means that the majority of top accounts currently active in the AI core circle are practitioners and entrepreneurs who have settled down after experiencing the PC, mobile internet, and Web3 cycles. When the large model wave came, they sensitively completed the migration of productivity tools.
- New Generation Growth in Chinese Zone: It is worth noting that during the ChatGPT explosion period from 2022 to 2023, the proportion of AI native new accounts that stood out in the Chinese zone reached 13.0%, higher than 9.7% in the English zone. This indicates that the Chinese ecosystem has given greater traffic dividends to practical content; as long as tools are proficient and tutorials are solid, new accounts can also build competitive advantages through continuous posting.
In contrast, the registration time of Web3 KOLs often presents a clear spindle shape, accompanying market heat with a large number of newly created accounts during DeFi Summer, NFT explosions, and Meme hotspots.
3. Symbiotic Evolution of AI KOLs and OPCs
The evolution of AI is turning the concept of One Person Company (OPC) from a superman-like concept into a reality that can be clearly implemented. The core essence of OPC is that the user sensitively calls various vertical AI Agents, thereby liberating themselves from fighting alone and undertaking all the hard and tired work, infinitely amplifying their own ideas, and using AI to complete independent product construction, commercial distribution, and precise marketing.
In this transformation, "Application Distribution" AI KOLs have站稳 the core ecological position with compound advantages:
- Understand Technical Boundaries: Most of them come from AI big factories or are senior developers, possessing underlying technical accumulation, and understand the real limitations of tools better than pure marketers.
- Understand Market Pain Points: As content creators who have long faced audiences directly, they possess strong productization and marketing awareness, and understand real needs better than pure R&D personnel.
It is precisely this double Buff of "technology + internet sense" that allows them to transform abstract technology into usable scenarios through Build in Public, thereby accumulating a steady stream of user trust.
The popular Vibe Coding trend has pushed the tension of this personal IP to the extreme: when a top AI KOL recommends a development framework, they no longer palely write a few recommendation words, but directly show on X how they collaborated with the model with only a piece of natural language instruction, accompanied by a relaxed atmosphere, to quickly launch a complete, interactive AI application within 15 minutes.
Traditional KOLs rely on distributing opinions to harvest traffic, while AI KOLs凝聚 ecosystems by distributing production capabilities.
4. Data Portrait: Ecological Divide Between Eastern and Western KOLs
To explore the real operating logic of the AI KOL ecosystem, this report extracted 100 tweet samples from the top 300 English zone and top 100 Chinese zone AI KOLs in the XHunt influence ranking within the last 3 months, and conducted deep calculations and comparisons on their tweet content and various data.
We found that Chinese and English AI KOLs show significant differences in attention structure and content production mode. The following will unveil the true face of AI KOLs for you one by one from seven core dimensions such as traffic market, discussion fields, account creation time, and personal profiles.
1️⃣Attention Map: English Zone Leans Towards Sources, Chinese Zone Leans Towards Practice
- Traffic Volume Distribution: The total fan volume of the English ranking market broke through 350 million, with an average of 1.17 million and a median of 110,669. The Chinese ecosystem leans towards refined vertical fields, with an average fan volume of about 77,000 and a median of 43,006.
- Posting Activity Comparison: Within the last 90 days, 100 accounts in the Chinese ranking produced nearly 30,000 tweets, with a median posting volume as high as 210. In contrast, 300 English accounts posted only 37,000 tweets in total, with a median of only 38. English top accounts are mostly in a low-frequency posting state, while Chinese accounts constitute a high-frequency application diffusion network.
- Fan Ladder Structure: The English ranking presents a pyramid structure, with accounts having 50,000 to 200,000 fans accounting for the highest proportion at 41.8%, and accounts with over 1 million fans accounting for 7.4%. The Chinese ranking is concentrated in the long-tail application layer, with accounts having 10,000 to 50,000 fans accounting for 53.0%, and only 4.0% having over 200,000 fans.
- KOL Followers: Although the mean peer follow count in the English ranking (510.7) is higher than in the Chinese ranking (320.2), based on the Chinese and English AI KOL base (approximately 1,000 and 5,000 respectively), the circle penetration rate of Chinese top KOLs is as high as 32%, far exceeding 10% in the English zone. This indicates that the Chinese AI KOL circle is a highly dense community with extremely tight connections.
- Activity Map: Up to 70% of Chinese KOLs share industry dynamics and practical operations high-frequency every day. Low-frequency active accounts in the English zone account for 39.8%, and stable active accounts account for 26.4%. The English zone leans towards an industry source network, while the Chinese zone leans towards a practice network.
Summary: English AI KOLs are an industry source network mastering first-hand technology and major strategic releases; Chinese AI KOLs are a super diffusion and practice network that crazily translates, evaluates, and tutorializes frontier technology and pushes it to public workflows.
2️⃣Mindset Preferences: English Zone Leans Towards Macro, Chinese Zone Leans Towards Practicality
Peeling away broad labels, through word frequency and label extraction of market discussion content, we clearly saw the focus of the two major Chinese and English ecosystems:
Whether in the English or Chinese zone, base models, AI Agents, AI commercialization, and AI programming are the consensus main axes, but the paths they extend outward are completely different:
- English Zone Focuses on Underlying Technology and Macro Perspective: English KOLs have coverage far exceeding the Chinese zone in AI commercialization (44.7%), base models (39.6%), AI safety (13.8%), AI chips (12.6%), and embodied intelligence (5%). They devote a lot of energy to discussing AGI safety alignment, computing power supply and demand patterns, open source vs. closed source games, and embodied intelligence.
- Chinese Zone Focuses on Application Landing and Practical Orientation: Chinese KOLs show extremely strong pragmatism. AI programming reaches 72.1%, basically twice that of the English zone. AI Agents are 51.5% vs. 39% in the English zone. In terms of visual generation, at 20.6%, the data is still close to twice that of the English zone. Tool evaluation is 11.8%, even more exaggeratedly close to nine times that of the English zone. Tutorials and prompts are also significantly higher than in the English zone, indicating that Chinese bloggers are better at breaking down complex technologies into specific operation guides such as code writing and Agent construction.
3️⃣Capability Radar: English Focuses on Technical Insights, Chinese Focuses on Full-Stack Applications
To reduce misjudgment of major categories, we called XHunt's KOL capability scoring model to conduct a comprehensive analysis of the content quality published by AI KOL accounts across multiple scoring dimensions:
- English Ranking Occupies Industry Sources and Underlying Logic: The highest score in the English ranking is Multimodal 88.3, followed by Base Models and Prompts. Their core capabilities are reflected in insights into model architecture, large-scale engineering tuning experience, and frontier trend prediction. In the fields of AI safety and chips, the English ranking has a natural first-mover advantage.
- Chinese Ranking Focuses on Full-Stack Application Practice: In the Chinese sample, the mean value related to AI programming capability reached 88.9, and AI Agents also reached 87.1. There are a large number of creators with natural language development capabilities active on Chinese Twitter; they are good at integrating AI into private domain monetization or light startup models.
4️⃣Large Model Mention Rate: Workflow Map Voted by Feet
The large model mention rate (i.e., any tweet from the account hitting a keyword within 3 months) represents not only the discussion heat of the large model itself in the community but also the "vote by feet" of KOLs on their dependence and praise/criticism trend of major models in actual workflows:
As shown in the figure, Claude and GPT constitute the kings of bilingual models. In the Chinese zone, the Claude mention rate is as high as 95.7%, still the first choice for independent developers and Vibe Coders; it is worth noting that with the continued heat of AI programming scenarios, Codex heat has soared recently, stabilizing at third place with a super high coverage rate of 80.9%, further confirming the Chinese geek's fanatic pursuit of landing workflows.
In addition, domestic large models DeepSeek (68.1%) and Kimi (58.5%) have also shown extremely strong local penetration. In contrast, in the English zone, GPT (76.2%) and Claude (75.2%) share equal power; compared to discussions of single tool chains, they focus more on multimodal evolution and the global narrative of the industry.
5️⃣MBTI Content Style: Account Expression Facets
Through an exclusive style inference algorithm, XHunt classified the public personality facets of Chinese and English KOL accounts into MBTI profiles based on AI KOL account bios, long tweet structures, interactive debate logic, and topic preferences:
As shown in the figure, regardless of the Chinese or English zone, accounts with discourse power mostly belong to the NT (Rational) camp. During the period of rapid technology iteration, content with logical analysis and productivity guidance is obviously more favored. The English ranking is dominated by ENTJ (38.4%) and ENTP (25.8%), leaning towards framework construction and macro analysis; the Chinese ranking is led by ENTP (41.2%), echoing the Chinese zone's enthusiasm for exploring diverse ways of playing with new tools.
6️⃣Identity Structure: English Leans Towards Frontier, Chinese Leans Towards Practice
Through clustering and cross-verification of the two sets of samples' Twitter account Profile bios and historical tweet self-descriptions, XHunt drew the map of Chinese and English AI KOLs:
Core Identity Structure:
- Over 65% of KOLs in the English zone are large model founders (31.4%), executives (34%), or scientists; their content output itself is a kind of strategic distribution.
- The top of the Chinese zone is Tools/Evaluators (69.1%) and Product Engineers (57.4%). Overall, the English ecosystem leans more towards a source release network, while the Chinese ecosystem focuses more on a productivity practice network.
Overall:
The English AI KOL network is more like a source technology and paradigm release network happening at the forefront of Silicon Valley, led by scientists and technical leaders; the Chinese AI KOL network is a comprehensive productivity tool and survival practice network exploding in the vast application market, led by full-stack independent geeks and application pioneers.
7️⃣Tweet Validity Evolution: From Wild Growth to High-Quality Development
Combined with the market trend of the last 8 months, the traffic distribution logic in the AI field has shifted from wild growth to high-quality development, and continues to improve in exposure and number of tweets, presenting three core characteristics:
- Attention Dilution in February & March: Affected by industry hotspots such as OpenClaw, the total number of tweets in March surged to 12.4K, and total Views reached 310M, but average Views per piece dropped to a low point (25.0K). A huge amount of homogeneous news flashes led to serious information overload and a decline in communication efficiency.
- Communication Efficiency Peak in May: The total number of tweets in May fell back to 9.0K, but total Views (335M) and average Views per piece (37.4K) both hit historical highs. Deep practice and evaluation content are leveraging greater traffic with fewer posts.
- Views Growth Rate Outpaces Tweet Production: As of the end of May, Views index growth (+88%) was significantly higher than tweet quantity growth (+62%). This indicates that the AI traffic dividend has still appeared with the 80/20 rule, rapidly concentrating on tweets outputting high-quality content with high premiums.
5. Authority Matrix: Global AI KOL Influence Electronic Business Cards
Based on the follow graph network, fan gold content, and content quality performance of Chinese and English AI KOLs, we specially customized an electronic business card for them using the AI favored by each top AI KOL.
Below is a list of the Top 20 most representative AI KOL business cards in the Chinese and English zones:
English AI KOL Top 20
- Andrej Karpathy @karpathy | AI KOL Followers: 1,444 | Followers: 2,358,391 Currently working in the Anthropic pre-training team, founder of Eureka Labs, former OpenAI founding team member, former Tesla AI head. A top evangelist who breaks down large model training, AI Coding, and Agents and feeds them directly to you, making engineers want to get up in the middle of the night to open an IDE.
- Sam Altman @sama | AI KOL Followers: 1,406 | Followers: 4,741,565 OpenAI CEO, absolute controller of GPT and Codex, a universe-level man whose single dynamic release makes half the AI circle automatically start highlighting key points.
- Greg Brockman @gdb | AI KOL Followers: 1,142 | Followers: 968,930 OpenAI President and Co-founder, the person who hardcore throws product, research, developer ecosystem, and infrastructure progress at you every day like an official construction log.
- Ilya Sutskever @ilyasut | AI KOL Followers: 1,069 | Followers: 664,828 SSI Co-founder, former OpenAI Chief Scientist, one of the most concerned researchers in the large model era, a deep thinking god whose casual remark can be interpreted by the whole circle for half a day.
- Jeff Dean @JeffDean | AI KOL Followers: 1,058 | Followers: 436,747 Google DeepMind/Google Research Chief Scientist, Gemini head, the hardcore navigator of where Google AI technology routes come from and go.
- Elon Musk @elonmusk | AI KOL Followers: 1,057 | Followers: 239,771,643 The super amplifier behind SpaceXAI, Tesla, and SpaceX, wanting models, robots, computing power, and platforms all together, a universe-level player whose single tweet is sometimes more explosive than a press conference.
- OpenAI @OpenAI | AI KOL Followers: 1,050 | Followers: 4,798,535 OpenAI official account, parent company of ChatGPT and Sora.
- Demis Hassabis @demishassabis | AI KOL Followers: 1,002 | Followers: 864,498 Google DeepMind CEO, super promoter of AlphaFold, scientific intelligence, and AGI narratives, Nobel Prize winner, letting AI truly move from chat boxes to scientific discovery.
- roon @tszzl | AI KOL Followers: 968 | Followers: 326,221 He observes the capability boundaries and safety issues of frontier models; comments are often sharp and insightful, liking to hit straight balls.
- Patrick Collison @patrickc | AI KOL Followers: 961 | Followers: 811,554 Stripe CEO, Arc Institute Co-founder, a macro perspective player putting AI into scientific organizations, infrastructure, and startup frameworks.
- Logan Kilpatrick @OfficialLoganK | AI KOL Followers: 957 | Followers: 304,209 Important communicator of Google AI Studio/Gemini API ecosystem, a practical hand pulling developer tools from magic back to products, code, and money.
- Yann LeCun @ylecun | AI KOL Followers: 947 | Followers: 1,144,073 AMI Labs Co-founder and Executive Chairman, former Meta AI Chief Scientist, one of the three giants of deep learning, Turing Award winner, a permanent resident of the debate table frequently speaking on AI routes, open source, world models, and the essence of intelligence.
- Mira Murati @miramurati | AI KOL Followers: 931 | Followers: 498,732 Thinking Machines Founder, former OpenAI CTO, a female leader at the forefront of computing power games and technology landing, leading the commercial pain and transformation of frontier models from labs to public workflows.
- Garry Tan @garrytan | AI KOL Followers: 892 | Followers: 779,149 Hardcore mentor of Silicon Valley's gold medal incubator, not following trends to shout slogans; he prefers to publicly demonstrate how he uses prompt engineering and personal AI systems to rub together a truly runnable architecture.
- Anthropic @AnthropicAI | AI KOL Followers: 884 | Followers: 1,216,610 Anthropic official account, Claude model developer, focusing on AI safety.
- Dwarkesh Patel @dwarkesh_sp | AI KOL Followers: 879 | Followers: 221,274 Host of top tech podcast Dwarkesh Podcast, hailed as one of the best dialoguers in the global tech community due to extremely deep and high-quality long interviews with AI core scientists and hardcore scholars.
- Alexandr Wang @alexandr_wang | AI KOL Followers: 878 | Followers: 444,108 Scale AI Founder, Meta AI head, occasionally releasing macro trends about underlying data labeling and the direction of traditional AI.
- Andrew Ng @AndrewYNg | AI KOL Followers: 870 | Followers: 1,499,288 Stanford University Professor, formerly led Google Brain and Baidu AI teams, a ballast stone and long-term evangelist for AI education and application landing.
- Aravind Srinivas @AravSrinivas | AI KOL Followers: 836 | Followers: 483,015 Perplexity CEO, a practical rewriter rewriting AI search and answer engines to redefine search entrances.
- Jim Fan @DrJimFan | AI KOL Followers: 819 | Followers: 396,349 Core figure in NVIDIA's robotics direction, top head player in embodied intelligence and physical world models.
Chinese AI KOL Top 20
- Baoyu @dotey | AI KOL Followers: 559 | Followers: 214,553 A hardcore translation super node in the Chinese-speaking circle, not engaging in metaphysical narratives, relying purely on first-time deep frontier paper breakdowns, top interview reviews, and out-of-the-box high-quality prompts, welding shut the bottom line of content quality.
- Orange AI @oran_ge | AI KOL Followers: 483 | Followers: 170,533 An Agent entrepreneur taking guns to the battlefield, combining geek rigor and business war acumen, always able to strip out the underlying business philosophy between Agent architecture evolution and organizational change.
- Guizang (guizang.ai) @op7418 | AI KOL Followers: 468 | Followers: 144,288 A "hexagonal warrior" in the independent developer circle, a dual-habitat hardcore player in visual generation and AI programming, helping countless people smooth out the pits of tool landing with massive practical tutorials and sharp-tongued evaluations.
- Bear Liu @bearliu | AI KOL Followers: 453 | Followers: 115,339 A super design geek in the AI era, playing Vibe Coding, Agents, and generative UI to the flower, deadlocking on how AI subverts traditional product development, pointing out the direction for independent creators.
- Baye @waylybaye | AI KOL Followers: 452 | Followers: 158,294 A benchmark for independent development with a distinct personality, not talking concepts, only talking practice, high-frequency output of various AI programming tool flesh-and-blood confrontation comparisons, tearing open the marketing camouflage of tools with plain language.
- Xiangyang Qiaomu @vista8 | AI KOL Followers: 441 | Followers: 107,140 A technical deadlock faction in the Chinese-speaking circle, good at chewing up the hardest multimodal frontier papers and feeding them to practitioners, using high-density tutorials and technical insights to pad developers' cognition.
- Ding @dingyi | AI KOL Followers: 431 | Followers: 151,205 An observer with extremely sharp technical and business olfaction, pixel-level disassembly of AI programming tools and transfer station ecosystems, always able to capture business opportunities missed by ordinary people in a complex table or marketing case.
- Tie Chuiren @lxfater | AI KOL Followers: 569 | Followers: 101.2k Continuously using AI for entrepreneurship, content, and product experiments, also maintaining high-star projects; not just shouting "AI changes the world," but already sticking hands into the mud to mix cement.
- Tw93 @HiTw93 | AI KOL Followers: 423 | Followers: 141,827 An extremely low-key but high-yield representative of independent developers, having both the hardcore foundation of large model training and the track record of personally rubbing out multiple high-value open-source tools, proving strength with code.
- Yangyi @yangyi | AI KOL Followers: 415 | Followers: 122,284 A business hacker combining technology and making money to the extreme, digging deep into the monetization limits of AI programming and Agents in private domains on one side, and suddenly reminding you of the blind spots behind technology from a security researcher's perspective on the other.
- yetone @yetone | AI KOL Followers: 413 | Followers: 82,680 A "hardcore deadlock faction" at the AI application layer, having extremely deep muscle memory in Agent architecture, Computer Use, and engineering practice of programming tools, attracting fans hardcorely 全靠 high-quality tool reproduction and evaluation.
- Mr Panda @PandaTalk8 | AI KOL Followers: 410 | Followers: 74,602 A "super connector" between frontier papers and landing monetization, good at translating the most academic Agent papers into grounded prompt techniques, looking coldly at AI commercialization and employment trends.
- Dash @DashHuang | AI KOL Followers: 408 | Followers: 113,575 A hardcore cross-border perspective of a big factory founder, deeply cultivating the limit squeezing of AI programming tools in traditional R&D and game development scenarios, providing weighty "regular army" landing references.
- Cell @cellinlab | AI KOL Followers: 407 | Followers: 26,667 A fanatic evangelist and practitioner of the "One Person Company" model, high-frequency testing of various AI programming tools and visual generation workflows, specially exploring the way for the commercial rise of super individuals.
- YC (Yucheng) @yucheng | AI KOL Followers: 393 | Followers: 18,728 An entrepreneurial thinker focusing on organizational change triggered by AI, not only deadlocking on the technical practice of tools like Claude Code but also obsessed with reshaping company operating efficiency with Agent architecture.
- Tualatrix @tualatrix | AI KOL Followers: 393 | Followers: 108,450 An "AI evolution sample" of old-school independent developers in the Chinese-speaking circle, high-frequency publicizing the real process of refactoring and developing independent Apps using Codex, Claude Code, concretizing the programming capabilities of large models.
- ruanyf @ruanyf | AI KOL Followers: 384 | Followers: 198,977 A lighthouse for Chinese-speaking developers with enduring technology, using an extremely sharp, macro perspective to continuously capture the destruction and reshaping of AI on the traditional software development industry, leading countless people to complete productivity leaps with solid tutorials.
- Xiao Hu @xiaohu | AI KOL Followers: 379 | Followers: 105,522 A "super intelligence station" and sharp-tongued evaluation officer in the AI tool circle, high-frequency scanning the latest programming tools and Agents across the network, always able to dig out the most grounded practical skills in unchanging news flashes.
- 𝗖𝘆𝗱𝗶𝗮𝗿 @Cydiar404 | AI KOL Followers: 378 | Followers: 62,106 A practical product engineer, not talking about ethereal grand visions, homepage full of hardcore flesh-and-blood evaluations of large models like Claude and life-and-death reviews of own API projects in business wars.
- Frank Wang Yubo @lifesinger | AI KOL Followers: 378 | Followers: 36,454 A super individual and long-termist entrepreneur in the AI era,揉碎 grand Agent architecture and product design concepts, breaking them open to publicly share how he uses a "One Person Company" to subvert traditional software development.
6. Heartfelt Journey of Excellent AI KOLs: Trust is Built on Continuous Verification
Cell @cellinlab ｜ Chinese AI KOL Influence Ranking: 15 | Founder of Creation Matrix Community
We will usher in an abundant era—people will make life more colorful through new channels of creation and self-expression, new paths of self-discovery and belonging, and new ways of carrying out meaningful work in life. Work needs to be redefined as creation: For a long time, our work was for survival. In the post-scarcity era, new work forms mean creation, growth, self-expression, and giving meaning to life.
Cuimao @CuiMao｜Chinese AI KOL Influence Ranking: 34 | AI KOL
"KOLs" in the AI industry are not just people with traffic, but those who truly participate in construction. Everyone recognizes me not only because I made many AI creative videos related to Anthropic, but more because they saw possibilities suitable for themselves from this content. Some started creating because of this, some understood tools because of this, and others therefore重新 believed: The AI era is not a card table for a few people, but a new classroom where everyone can be seated again.
I clearly feel that public influence in the AI era is no longer just about being seen, but about letting more people see their own positions. It is not a life-and-death challenge of grabbing chairs in "Squid Game," but a reseating for a new semester. Positions will change, order will change, but everyone still has the opportunity to find their own coordinates.
So, if I were to summarize my attitude towards this era in one sentence: Keep the love, learn, create, share.
Asa @app_sail ｜ Chinese AI KOL Influence Ranking: 52 | @app_sail, tutti.so Partner
Initially starting to share was actually Build in Public, not to become a KOL. Because I have long been in the front-line practice of AI global expansion, global payments, and 𝕏 operational growth, every time I verified a path or stepped into a pit, I would record and share it, slowly finding myself becoming an AI KOL.
These shares also made me more and more certain: The attention economy era has arrived; every individual, every product, every organization should actively manage their own influence.
In my opinion, KOLs are more like connectors, connecting information and cognition, connecting products and users, and connecting people from different cultural backgrounds. Although AI makes content production more efficient, real experiences, insights, independent judgments, and long-termist persistence are still scarce.
It is also based on this cognition that we created tutti.so, hoping to help more Chinese enterprises and creators build global influence, letting good products and good stories be seen by the world. In the future, what is truly scarce is not traffic, but trust.
Jason Zhu @GoSailGlobal ｜ Chinese AI KOL Influence Ranking: 71 | Founder of GoSail Lab, AgentSkillsHub
Exploring all the way, receiving the big gift package at 31, jumping from orbit into the wilderness, only then realized: KOL for me is not a persona, but recording the real exploration path.
My understanding of KOLs has just two points:
- Authenticity is the bottom line: Do not write unverified second-hand content; profits from shoe flipping, losses from escape rooms, growing followers from zero, all are run out by myself.
- Leverage is the method: AI speeds up, I steer. Deep playing OpenClaw, Claude Code, built agentskillshub.top, putting soul is the engineer's seriousness. People who open source real experiences are the scarcest products in the AI era.
Gorden Sun @Gorden_Sun ｜Chinese AI KOL Influence Ranking: 75 | AI KOL
I have been writing AI news daily for over 3 years; stick to simple and altruistic things, and you can become a KOL too. Writing daily reports every day also allowed me to accumulate best AI practices in various scenarios; I shared almost everything without reservation. Altruism, sincerity, writing some useful shares as much as possible, this is the creed I believe in. In the AI era where software products are easier to build, distribution and marketing are increasingly important; everyone should try to do some sharing; this is a compound interest thing, and you won't have any losses.
Yu Zong Talks AI @AI_Jasonyu ｜Chinese AI KOL Influence Ranking: 84 | AI Global Expansion KOL
Creating the "Yu Zong Talks AI" IP was initially just to share tools I thought were good and pits I stepped into. Later, receiving more and more feedback, I realized that one piece of real practical content can really save others a lot of time and cost.
I always feel that a KOL is not standing high teaching others, but going into the field first for everyone, trying new tools and new opportunities personally, and then explaining the truly useful methods clearly. Along the way, my positioning has become clearer and clearer: Focus on AI, global expansion, and products, only sharing content I have researched, practiced, and can solve real problems.
AI can improve efficiency, but cannot replace human judgment and experience. Compared to pursuing rankings, I hope to be a credible, practical information source in the long term, helping ordinary people truly use AI well and avoid detours.
Defou @wangdefou ｜ Chinese AI KOL Influence Ranking: 101 | Founder of Defou Tech, Enterprise AI Application Consultant
I always feel that a KOL is not a "person who posts content," but a person who continuously accumulates trust in the public field.
Because I am a liberal arts student, growing followers on X was very slow at first, taking three years to reach 5,000 fans; intermittently stepped into many pits in between. Later, what really made me grow was not algorithm metaphysics, but authenticity, sincerity, and continuously outputting things useful to others.
Now AI is developing so fast; various tools can help us collect information, organize materials, and improve efficiency, but it is ultimately a tool and cannot replace a person's judgment, experience, and expression.
My positioning is very simple: Use a liberal arts student's perspective to make AI tools, content creation, and personal commercialization these things more grounded. Being able to help more ordinary people avoid detours, and incidentally meet a group of people who are truly doing things, I think this is the most interesting part of being a KOL.
Recently busy with offline business, Twitter operations have been a bit slack.
Star @starzq ｜ Chinese AI KOL Influence Ranking: 262 | Founder of @day1globalpod
In the AI era, everyone is anxious: Why can others use large models better, buy 10x stocks. But I want to say, AI is a super long cycle; laying a good foundation at the beginning of the cycle allows you to enjoy more era dividends. I hope my shares can let everyone understand all aspects of the AI cycle more deeply, using AI without anxiety.
qinbafrank @qinbafrank｜Chinese AI KOL Influence Ranking: 287 | AI Macro Blogger
Actually, I personally consider myself more of a blogger than a KOL; recording real thoughts and reasoning chains, first serving my own research and investment,其次 helping everyone identify truth and think rationally in the information flood.
The AI era greatly accelerates global information integration, code verification, and trend disassembly; we need to master the core even more: AI can greatly improve efficiency, but human judgment, experience, thinking chains and logical chains, analysis frameworks are instead scarcer. Focus on truth seeking and practical insights. Share verifiable frameworks and practical thinking, not simple conclusions, helping ordinary people truly use AI well and avoid detours. Hope to be a credible, rational thinking partner in the long term.
XinGPT @xingpt｜Chinese AI KOL Influence Ranking: 359 | Former VC Fund Partner, AI KOL
The original intention at the beginning was to use AI to bring financial equity: Ordinary investors can also use AI to wrestle with professional investors. Currently, we have developed various tools such as AI industry research, AI market tracking and review, AI real-time reminders, etc., and practical effects are gradually improving. I dare not imagine how to complete so much industry research work without AI. In the future, we will gradually mature these tools and open them; welcome investment and AI experts to communicate.
Crypto_Painter @CryptoPainter｜Chinese AI KOL Influence Ranking: 490 | AI KOL
Although not strictly an AI blogger, the improvement AI brings to me far exceeds the past ten years...
When hiring a human to engage in non-physical work for you, what you are hiring is actually his brain, a neural network composed of tens of billions of neurons, a carbon-based large model, and 60% of the computing power is still unrelated to work...
And AI and Agents can perfectly replace this role, completing better work with higher efficiency.
So I have been persisting in converting most non-physical work to AI execution; data analysis is completed by exclusive Agents, quantitative trading is monitored by AI, and even tweet inspiration is content processed by AI...
I do AI-related sharing not purely to follow traffic and attention, mainly because I had a baby this year, simply don't have that much time and energy to do so many things, and the emergence of AI Agents saved me a lot of time!
This is a magical experience I completely could not imagine before; I sincerely recommend and encourage everyone to try handing over non-physical, simple repeatable tasks in their daily work and life to AI; the happiness brought by this freedom is true happiness.
Haotian @tmel0211｜Chinese AI KOL Influence Ranking: 570｜Amber Consultant
Actually being a KOL is using "output to force learning," accelerating my understanding of various industries and even industrial upstream and downstream, thereby harvesting investment dividends from cognitive monetization.
In the past two years, I seized the rapid iteration and hype dividends of Crypto industry technical narratives, becoming a hardcore technical blogger in everyone's minds, but in the past half year Crypto market cooling, market attention returned to the AI tech main line narrative, I also started transforming from zero, setting sail again, thinking and tracking the entire AI tech main line with a brand new industrial insight perspective, including semiconductors, robots, chips, storage, etc.
Of course, this process was very painful because many industrial upstream and downstream were completely unfamiliar to me; I found that in the process of deadlocking on the industry, the things I could output became less and less; most of the time was silently investing and trial-and-error, then following my portfolio to explore and research across the entire industry. The result was of course beyond my expectation; not only had unexpected investment profits, but also changed my固有 cognition of original KOLs; it turns out the important thing is not whether to output or not, but how to timely refresh your own "input"; only letting yourself forever possess thoughts and think tanks that do not fall behind is the true confidence of being a KOL.
DeFi Teddy @DeFiTeddy2020｜Chinese AI KOL Influence Ranking: 666 | Founder of Biteye/XHunt
In the AI era, becoming an excellent KOL requires understanding and leveraging AI to improve content production efficiency, such as using AI to collect information and conduct preliminary analysis, using AI for article topic selection, etc.
However, AI is only our co-pilot; it can only be in the co-pilot seat and cannot control the overall situation. Truly valuable content requires KOLs to generate their unique perspectives and analysis based on AI analysis, showing the KOL's own "soul."
Anita @Anitahityou｜Chinese AI KOL Influence Ranking: 895｜Head of Senitent APAC, AI KOL
There are thousands of KOLs, but truly those coming from personal viewpoints are few. To be a minority, people follow you not to see千篇一律 information, but because you Build In Public or because you can see the essence through phenomena. Committed to being an ordinary person with independent thinking. Communication is for growth.
7. Paradigm Divide: AI KOLs vs. Web3 KOLs Showdown
Although AI KOLs and Web3 / Crypto KOLs, which have also been popular on Twitter in recent years, are in the same X social ecosystem, the axis of influence operation and survival monetization logic of the two have essential differences.
The essence of Web3 KOLs is a distribution network of opportunities and capital. Influence stems from the breaking of information asymmetry, the amplification of wealth effects, and the mobilization of community emotions. Its core assets are "news" and "calling power," and the value realization path is usually project promotion, token distribution, and community construction.
The essence of AI KOLs is a distribution network of productivity and capabilities. Influence is anchored in verifiable, reproducible real capabilities. They do not provide get-rich-quick passwords, but efficiency tools and usage methods. Its core assets are "trust" and "methods."
In 2026, the two circles are undergoing interesting edge interweaving: some sensitive Web3 accounts have started using AI Agents to automatically monitor chain anomalies and batch create accounts; some Web3 KOLs have also started transforming into AI KOLs. But ultimately, the evergreen influence of AI KOLs must be firmly anchored on "verifiable real capabilities."
8. Finally: From the Information Age to the Trust Age
In the past twenty years, the core problem solved by the internet was: How information spreads.
In the AI era, the fundamental problem it is solving has become: How capabilities spread.
In this grand transformation, a new scarcity is emerging: Trust.
Because AI can generate content, generate code, generate summaries. But it can never generate real experiences, trial-and-error paths, verification processes, long-term consistency.
The core of future influence is no longer information volume, fan count, or propagation speed, but: Are you continuously, publicly, verifying and delivering results to the real world.
The true discourse power of the AI era does not belong to the strongest expressers, but to those who continuously build trust networks.
Research Statement:
- All research conclusions, percentage distributions, and scoring results in this report are generated based on data as of June 2026 and do not represent the long-term, unchanging fixed influence ranking of each account. Statistics Date: March-May 2026.
- The identity classification and MBTI attributes involved in this report are AI model algorithm inferences based on public tweet behavior characteristics, used to macroscopically present the content ecological portrait of the group, and do not represent their real test results or professional identity certification in the real world.
About XHunt
XHunt is an industry-leading, AI-driven social intelligence and KOL influence analysis tool. Committed to providing the most real and authoritative KOL measurement indicators and account holographic portraits for the global Web3 and AI ecosystems.
- X/Twitter: @xhunt_ai
- Official Website: https://xhunt.ai/
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