The 120 Chinese Creators on X Worth Following in 2026 (AI, Open Source & Going Global Picks)

A few days ago, I published The 100 AI Creators Worth Following on X in 2026. After it went out, plenty of people asked: is there a Chinese-language version?

So this time, I did a deep dive into hundreds of Chinese-language X accounts, verifying each one’s work one by one.

I originally planned to keep just 100, but everyone was so good that I ended up keeping 120.

Coverage spans AI, open source, going global, development, and investing. I’d suggest bookmarking it first, then following accounts as you need them. https://t.co/tNP6hFFVcD

The 120 Chinese Creators on X Worth Following in 2026 (AI, Open Source & Going Global Picks)

A few days ago, I published The 100 AI Creators Worth Following on X in 2026.

After it went out, a lot of people commented that a list like this was sorely needed. What surprised me more was that the list introduced me to many excellent creators I had never come across before.

So this time, I decided to go through Chinese-language X accounts from scratch and compile a list of Chinese creators and builders worth following long-term.

I still originally wanted 100 people.

For this list, I went through hundreds of Chinese-language accounts, verifying public identity, representative work, recent content, and long-term focus areas one by one. I cut people from this list over two or three rounds, and 120 remained.

I simply couldn’t cut any more.

If I had forced the number down to a clean 100 just for symmetry and dropped 20 more people who have genuinely built real things, there’d be little point. So this time I’m not rounding down — I’m keeping 120.

These 120 aren’t just AI bloggers. They include open-source authors, indie developers, researchers, and industry analysts. The numbering is not a ranking of ability, and follower count is not a hard threshold. What matters more to me is whether someone has real work, first-hand experience, and whether you can follow their content back to the source.

If you’re looking for a batch of long-term Chinese X accounts that are worth your ongoing attention, this list should save you a good amount of screening time.

How Did I Pick for This List?

Real work first. Products, code, papers, long-running columns, blogs, course systems, public reports — anything traceable carries more weight than a claim of “really understanding AI.”

First-hand experience matters. People who have actually built models, shipped products, gone global, led organizational transformations, or maintained open-source projects take priority over people who just relay news.

Follower count is not a hard threshold. A small account with substantial work stays in; a large account that has drifted off-topic or stopped producing won’t get in automatically just because of fame.

Topic boundaries kept as tight as possible. Accounts whose main content is political commentary are not included, nor are crypto accounts focused primarily on trade calls and market predictions. For Web3, only two slots were reserved — one for security and one for protocol research.

Every account was re-checked. Mainly verifying public identity, representative work, recent content, and topic consistency. Unverifiable self-reported income, follower counts, and project star counts are not grounds for inclusion.

This is not a power ranking from #1 to #120 — the numbers are just for easy reference. Each group solves a different problem, so start following whichever group you need most right now.

9 Categories at a Glance:

AI Products, Startups & Organizational Adoption (16): Product decisions, enterprise transformation, organizations, and commercialization.

Going Global & Indie Development (15): SEO, GTM, sites, SaaS, and global distribution.

AI Research, Models & Hardware (13): Papers, inference, training, on-device, and infrastructure.

Agent Engineering & AI Development (18): Agents, AI coding, deployment, and hands-on testing.

AI Content, Visuals & Tool Testing (16): Chinese-language explainers, workflows, design, and multimodal.

Open Source & Infrastructure (15): International open source, databases, frameworks, and engineering governance.

Programming & Developer Tools (15): Long-term technical writing, tooling products, and security.

Investment, Industry & Long-Form Writing (10): Macro, earnings, supply chains, AI governance, and long-form writing.

Web3 Security & Protocols (2): Offensive/defensive security, wallet security, and protocol mechanics.

Total: 120 people, covering 9 categories across the Chinese tech and AI ecosystem.

1. AI Products, Startups & Organizational Adoption

This group cares about more than model parameters — they focus on how AI gets into products, teams, and revenue. If you build products, lead teams, or are driving AI transformation at a company, start here.

1. SituK @isituking

That’s right, I’m putting myself first 😂. I’ve been doing startups and enterprise services for over ten years. Right now I mainly research Skill × Agent, enterprise AI adoption, and GEO, openly sharing methods, processes, and pitfalls from real projects. If you want to see how AI moves from demos into real business, follow me.

2. Yiren @yiren_ai

Founder of ShengCai YouShu (生财有术), pushing AI-native transformation deep into his organization. What’s worth watching isn’t just his judgment on opportunities, but how a mature community and team rebuild processes, roles, and delivery.

3. Fu Sheng @FuSheng_0306

Founder of Cheetah Mobile, who has long publicly shared firsthand practices of mature companies transitioning to AI Native. If you want to see how large teams adjust products, organizations, and resource allocation, his retrospectives are very instructive.

4. Liu Xiaopai @bourneliu66

Liu Xiaopai has made Building in Public a daily habit. Product code, changelogs, growth processes, commercialization details — he’s willing to lay them all out. For indie developers, this kind of continuous record is far more useful than a single success-story retrospective.

5. kevinzhow @kevinzhow

The independent product mind behind KanaOrigin and Miraa, hands-on across design, engineering, and commercialization. If you want to see how a product starts from aesthetics and experience and gets refined step by step until people are willing to pay, keep a close eye on his updates.

6. Yao Jingang @yaojingang

Author of GEOFlow, who has shared multiple enterprise-grade Skills and overseas SEO playbooks. He’s good at tying GEO, Agents, and enterprise workflows together — what he discusses goes far beyond surface-level traffic tricks.

7. Saito @SaitoWu

Founder of Podwise. How to find product positioning, how to iterate, how to face real users — he covers all of this concretely in his startup and commercialization retrospectives.

8. Jin Chen Ma @jinchenma_ai

Consistently breaks down one-person companies, cutting-edge deployment-based delivery, and independent commercialization cases. The strength of his content is grounding abstract trends in concrete questions like customers, pricing, delivery, and payment collection.

9. Cold Cat IcyCat @icycat

Turned pain points around content discovery and creation on Chinese X into products like X Viral Monitor, while also building X Article and Obsidian-related tools. He both publishes methodology and actually ships products.

10. Zhao Chunxiang @chunxiangai

Author of Laper and Bellybook, frequently sharing how to use Agents to quickly build and iterate products. Content focuses on need assessment, technology selection, and shipping cadence — good for those following AI-assisted product development and delivery.

11. Yu Bo @lifesinger

A key founder behind Yuque and Ant Design, someone who has navigated big-tech product and organizational governance firsthand. Watching him discuss Agents, products, and human collaboration now, his eye is far sharper than the trend-followers’.

12. Ding @dingyi

Curator of the DEX Weekly, a rare durable information source in the Chinese product design space. His selections are restrained — new tools alongside interaction and aesthetic judgment. Well worth adding to any product and design professional’s regular reading list.

13. Owen Young @OwenYoungZh

Founder of Immersive Translate. Although his X updates aren’t especially frequent and most of his writing lives on his personal site, whether it’s real product delivery or indie development thinking, he’s a builder worth following to the source.

14. AYi @AYi_AInotes

Studies organizational development, prompts, and AI business adoption together, focusing on how AI actually enters real organizations. Her content connects technological change to roles, collaboration, and organizational growth.

15. Cell @cellinlab

Host of the Maker community WuWuJuZhen and the XiaoHuoLu podcast, always connecting creators, products, and new technologies. Content spans AI, personal creation, and crypto — a great window into the emerging generation of independent creators.

16. Guan Si @guansi

Focused on multi-agent orchestration, digital employees, and productivity tools. Recent posts on orchestrating Codex with Opus, running local models, and multi-Agent collaboration are impressively hands-on. On the side he writes sci-fi and games — beyond the technical foundation, he has real product intuition.

2. Going Global & Indie Development

This group is closer to “now that you’ve built it, how do you sell it.” From keywords and SEO to GTM, subscriptions, payments, and global distribution — these are lessons every indie developer will eventually need to learn.

17. Ge Fei @gefei55

Going global, SEO, keyword research, site operations — Ge Fei covers all of it with frontline, hands-on experience. Beginners can build a foundation from his content; veterans can observe how traffic tactics evolve.

18. viggo @decohack

Has spent years curating indie products, navigation sites, and practical tools. Whether you’re looking for topic ideas, studying product forms, or judging whether a small tool is worth building, browsing his account is extremely efficient.

19. sitin @sitinme

Founder of HiAPI.ai, regularly sharing AI going-global, growth, community operations, and multi-site practice. Content is very close to the business frontline — if you’re working on APIs, tool sites, or overseas customer acquisition, you’ll find it highly relatable.

20. Viking @vikingmute

Breaks full-stack SaaS development into a series of tutorials and has his own product launch experience. He walks you through everything from writing pages to tech stack selection, product build-out, and final delivery.

21. Yangyi @yangyi

Currently building NewMax, mainly sharing GTM, growth, and commercialization transformation practices for overseas AI software. A good fit for those interested in how Chinese teams enter overseas markets, define product positioning, and drive sales.

22. Baye @waylybaye

From Panda Eat SMS to ServerCat and OpenCat, he consistently lays out the technical and product trade-offs of indie development. His projects span a wide range, but underneath they all circle the same thing: building products around real pain points.

23. JJ Ying @JJYing

Co-host of Anyway.FM and creator of design and content projects like Anyway.Fonts and Momoyu. A good follow for designers interested in combining aesthetics, content output, and small indie products for long-term compounding.

24. Yu Wen @gkxspace

AI products, overseas infrastructure, startup projects — he’s willing to dissect them all. Deployment costs and real-world pitfalls are written in especially concrete detail, making his posts easy to mine for actionable leads when building overseas products.

25. Fox @indie_maker_fox

Author of MkSaaS and TanStarter, tightly combining SaaS engineering with indie development. He’s carved a clear path for chaining scaffolding, product development, and commercialization into a reusable playbook.

26. Yu Zong Talks AI @AI_Jasonyu

Focuses on overseas products and subscription monetization, and has compiled and openly shared practical case libraries like Paywall Gallery. Reading his tweets, pay attention to details that affect revenue: how to set up paywalls, how to price subscriptions.

27. Zili @hzlzh

Author of MenubarX, Lock Launcher, 2Camera, and other products, with long-term focus on indie product development and global distribution in the Apple ecosystem. A good follow for those interested in interaction design, feature definition, and commercialization practices for small utility products.

28. Lao Yang | AI Product Commercialization @yhslgg

Uses years of startup experience to break down product opportunities and monetization paths in the AI era. His opinions are sharp and direct — great for breaking mental ruts and doing the economic math on a project.

29. droidHZ @hezhiyan7

Documents the process of taking websites overseas — site building, SEO, and cold-starting from zero — in real time. The scale may not be large, but every step is traceable, which makes it more useful for beginners than grand narratives.

30. huangserva @servasyy_ai

Brings both a programmer’s and a founder’s perspective, documenting AI going global and product practice. Posts include both technical implementation and business wins and losses — you can see how a veteran entrepreneur repositions himself in the AI wave.

31. YC (Yucheng) @yucheng

Deep in AI solo entrepreneurship, community building, and overseas products. Public projects include TuttiHQ, LuciusHQ, and more. If you want to see how a one-person company operates or how overseas products cold-start, check his feed regularly.

3. AI Research, Models & Hardware

If you don’t just want to follow product launches, look at this group. They dig straight into papers, model architectures, inference systems, hardware, and on-device deployment — among the closest to the technical source in the Chinese-language community.

32. Dong Xi @dongxi_nlp

Primarily breaks down KV Cache, attention, and on-device deployment, walking through mathematical derivations and code step by step. The content has some depth, suited for readers who want to deeply understand model inference efficiency and underlying mechanisms.

33. yan5xu @yan5xu

Has frontline Agent R&D experience and frequently shares system retrospectives and engineering judgment. A good follow for those interested in how Agent products handle architecture design and reliability when moving from demos to complex tasks.

34. Wey Gu @wey_gu

His domain is the convergence of GraphRAG, knowledge graphs, and vector databases. If you’re building enterprise retrieval, knowledge engineering, or Agent memory, you can follow his articles to assemble a complete technical map.

35. karminski-牙医 @karminski3

Co-founder of KCORES, mainly sharing hands-on tests of GPU clusters, AI hardware, and infrastructure. He frequently compares hardware performance through real-machine testing and benchmark data — great for readers interested in real compute hardware performance.

36. Fu Yao @Francis_YAO_

NVIDIA researcher with published papers on large model inference, scaling laws, and complex reasoning. If you want to follow the research frontier with Chinese-language explanations, follow his papers and long threads.

37. Ni Hui @nihui

Core author of ncnn, working year after year on mobile and embedded AI inference. How on-device models actually run, how to optimize them, what the engineering reality looks like — his code and projects speak more directly than slogans.

38. Su Jianlin @Jianlin_S

Co-author of RoFormer/RoPE, who for many years has publicly worked through model architectures, optimization methods, and long-context problems on “Science Space” (科学空间). Chinese-language AI theory writing of this caliber is rare.

39. Zhao Chenyang @GenAI_is_real

Core lead and main maintainer of SGLang-Omni, regularly sharing engineering progress on multimodal inference. A good follow for those interested in how speech, images, and text plug into a unified inference system and for tracking related open-source projects.

40. Han Xiao @hxiao

Founder of Jina AI, deep in neural search, embeddings, rerankers, and Agent experiments. With both an academic foundation and a team competing in the commercial arena, you can see how cutting-edge technology actually lands as a product.

41. Yuandong Tian @tydsh

Research spans reinforcement learning, multi-agent systems, and large model training. Public work includes Coconut, StreamingLLM, GaLore, and more. Much of what he outputs is fundamental research judgment — very satisfying reading for those with some model background.

42. Yaowei Zheng @code_hiyouga

Author of LLaMA-Factory. That single piece of infrastructure — used by large numbers of developers worldwide to train and fine-tune open-source models — alone cements his weight in the Chinese open-source community.

43. Xinyu Zhou @zxytim

Co-founder of Moonshot AI (月之暗面), often discussing the large model systems, engineering tools, and open-source practices behind Kimi. Here you can see how a frontline core team builds systems — far from a simple official press-release machine.

44. Yanhua @yanhua1010

Frequently uses code and hands-on testing on his personal site for model comparisons and Agent breakdowns. Take his evaluations as selection references, then go to the original projects and try them yourself — it’ll save you a lot of detours.

4. Agent Engineering & AI Development

This is the largest group on the entire list. Because in 2026, what truly sets people apart is no longer whether they can chat — it’s whether they can make Agents reliably write code, call tools, run workflows, and deliver.

45. Hua Shu @AlchainHust

Author of Nuwa and other projects, working on both open-source engineering and AI product adoption. What he talks about most is how Agents and automation actually plug into a product loop — never limited to showing off a few prompt tricks.

46. Wang Shuyi @wshuyi

A university instructor who combines research, knowledge management, and large model applications into daily teaching and writing practice. His articles are well-organized, often publishing concrete operational steps and workflows — a good follow for those in academic and knowledge-work scenarios.

47. hidecloud @hidecloud

Co-founder and CPO of Manus, sharing Agent product decisions from a product leader’s perspective. If you want to observe how a frontline team defines Agents and handles general capabilities vs. product boundaries, follow him.

48. Leo Xiang @leeoxiang

Focused on WebRTC, real-time audio/video, and the underlying SDK infrastructure for voice Agents. The hardest parts of voice Agents — latency, interruption, transport, and engineering stability — he can dissect all the way down to the infrastructure layer.

49. Digital Life Kazik @Khazix0918

One of the representative authors of Chinese-language multimodal hands-on reviews, also maintaining hot resource libraries like AIHOT. His strengths are speed, volume, and intuitive comparisons — when a new model drops, checking his first wave of hands-on tests saves time.

50. Jiu Yuan Ke @9hills

Focused on security, compliance, and risk-control architectures for enterprise-grade Agents. While everyone else is talking about “can we do it,” he reminds you to also ask “who’s responsible when something goes wrong, and how do we audit it.”

51. Tom Huang @tuturetom

Advocate of Open Design and an Agent builder, constantly exploring Agent interaction forms. Agents need more than raw underlying capability — they need interfaces people can understand and control. That’s his domain.

52. Ameliayu @ameliax111

Focused on AI-native organizations, human-AI collaboration, and team transformation research. She excels at breaking down the seemingly abstract notion of “AI changing organizations” into concrete roles, collaboration relationships, and delivery processes.

53. Fan Kai Talks AI @fankaishuoai

Early founder of JavaEye, who brings a veteran technologist’s time horizon when judging large models and product evolution. Comparing his viewpoints against short-term hype makes it easier to distinguish real change from mere noise.

54. Tie Zhu AGI @cgnot996

Author of Grok App, a third-party cross-platform open-source client, continuously maintaining installers, docs, and issues (not an official xAI product). The draw is his solid cross-platform development and open-source maintenance skills.

55. Lan Ge AI @0xlangeai

Regularly publishes Chinese-language tutorials and configuration templates for tools like Grok Bot, Codex, and Cursor, with detailed step-by-step breakdowns. A good follow for readers who want to quickly grasp how to use new tools and set them up.

56. Xue Ta Wu Yun @Pluvio9yte

Frequently tests Agent workflows, local deployment, and video generation tools, with some repositories open-sourced. Content includes plenty of concrete hands-on processes, test results, and analysis of tool limitations — good for those interested in frontline practical experience.

57. Practice Ge Li @MinLiBuilds

For local large models, AI Agents, and AI video tools, he generally installs first, runs first, then draws conclusions. When you need deployment steps or side-by-side comparisons, this kind of record saves a lot of time.

58. Mu Ma Ren @cnyzgkc

Tests model applications and builds automated workflows from an engineer’s perspective. No grand concepts — whether something works or where it breaks, he lays it out clearly in a few sentences.

59. Tie Chui Ren @lxfater

Shares practice around AI-assisted startups and open-source projects, frequently publishing his own product progress, code repositories, and iteration logs. A good follow for those wanting to observe indie development and AI application adoption through concrete projects.

60. Yi Chen @gengdaJ

Continuously refining yichen-skill and Agent memory systems. If you’re thinking about how to make a personal Agent accumulate context and support long-term collaborative companionship, you can follow his repositories directly.

61. Li Jiu Er @li9292

Documents his full journey of learning AI and building products in real time as an “agentic coder.” No lofty lectures — just an ordinary developer using Agents to push real projects live, step by step.

62. meng shao @shao__meng

Focused on Agent building and AI coding, skilled at breaking down first-hand overseas materials into engineering architectures, tool selection, and enterprise cases. His profile states he previously served as CTO and currently works as an AI technical consultant and corporate trainer.

5. AI Content, Visuals & Tool Testing

Someone has to build the models, and someone has to explain them clearly, make them usable, and turn them into creative work. This group covers Chinese-language explainers, visual generation, prompts, multimodal, and tool curation.

63. Baoyu @dotey

When overseas AI papers and first-hand engineering materials reach him, they often become clearly structured Chinese-language explanations. Speed is only the surface — what’s more valuable is that he explains context, key changes, and real-world impact clearly.

64. Gui Zang @op7418

His AIGC Weekly gathers the week’s new models, tools, and workflows into one newsletter, and he additionally produces prompts and skills. However fast the Chinese AI space changes, a weekly scan of this issue keeps you on the main thread.

65. Orange AI @oran_ge

Founder of ListenHub and ColaOS, frequently doing retrospectives on first-line decisions and building processes behind AI products. You can see both how content products get made and how AI-native interaction gets implemented.

66. Li Jigang @lijigang

Systematized prompt design early on, using cognitive cards to force deeper thinking. Don’t just look at him to copy ready-made prompts — the real lesson is how he takes a tangled mess of abstract thought and tightens it into a single clear expression.

67. howie.serious @howie_serious

Blends AI adoption, cognitive science, and personal workflows into a system he calls Feynman OS. He cares about how people use AI to think problems through deeply and learn thoroughly — not just shaving a few minutes of surface efficiency.

68. Zho @ZHO_ZHO_ZHO

Doggedly works on ComfyUI visual generation workflows and open-source nodes — an unavoidable name in the Chinese AI visual space. If you want to go from “randomly gacha-ing images” to “precisely controlling flow and stably reproducing results,” dig straight into his repositories.

69. Xiang Yang Qiao Mu @vista8

Closely tracks GEO and enterprise AI adoption, skilled at translating cutting-edge concepts into business actions. Two threads he’s bitten down on hardest: how brands squeeze into AI’s answers, and how enterprises actually put new tools to use.

70. Liu Jiang @turingbook

Veteran technology publisher and industry organizer, having observed the tech industry and developer ecosystem for many years. Rather than chasing individual tools, he’s better at helping you see how tech waves gradually permeate publishing, communities, and entire industries.

71. Rion Wu @rionaifantasy

Mainly plays with AI automation, 3D modeling, imagery, and game production. Recently released practical records like a partial image-editing skill and 3D mini-games. You can see the finished products — and you can see how the process from idea to execution actually gets ground out.

72. Sac @Saccc_c

Combines AI, Blender, and 3D to create playable projects — The Little Prince: Across the Stars is currently his most striking representative work. What he delivers isn’t a static demo image, but a 3D experience you can jump into and run directly.

73. Berryxia.AI @berryxia

Blends design and programming, frequently posting generative design applications and system prompts. Visual creators and product people can mine them for workflow inspiration and adapt them into their own versions.

74. Call Me A Hang @Astronaut_1216

Tests models and breaks down prompts from a product manager’s perspective. When a new tool comes out — what can it actually do, where are its capability boundaries? His hands-on tests reveal the true picture quickly.

75. Li Yue @liyue_ai

Has deep hands-on self-media experience, focused on prompts, model evaluations, and skill creation. If you want to genuinely integrate AI into your daily content production pipeline, start with his concrete tutorials.

76. Huang Yun @huangyun_122

Specializes in hands-on prompts and model applications, habitually starting from small, specific tasks and directly giving steps you can follow. When you’re first getting started building a personal AI workflow, browsing his posts makes it easy to jump in.

77. Gorden Sun @Gorden_Sun

Maintains a daily AI news roundup, curating new models, open-source projects, and tool updates with brief interpretations and some hands-on testing notes. A useful source for tracking industry developments and discovering new projects day to day.

78. Adrian Punk @AdrianPunk115

Author of Punk-Skill and multiple visual skills, packaging AI visual techniques into ready-to-run tools. For people just starting to explore visual workflows, his work and tutorials are intuitive enough.

6. Open Source & Infrastructure

Many in this group don’t have inflated follower counts, but their work has already become part of countless developers’ daily routines. When looking at open-source figures, it’s best not to ask how many followers they have — ask what they’ve maintained, and for how long.

79. Ruan Yifeng @ruanyf

Author of Tech Fan Weekly (科技爱好者周刊), maintaining tutorials, blogs, and public documentation like clockwork for over a decade. To countless Chinese developers, he’s long since become more than an account — he’s a continuously operating lighthouse of technical information.

80. Evan You @yuxiyou

Creator of Vue.js and Vite. Beyond technology, this Chinese-language account also discusses products, open source, and personal judgment. If you want to follow more comprehensive technical developments, continue through his projects and English-language content.

81. Anthony Fu @antfuzh

Author of Vitest, Slidev, VueUse, UnoCSS, and more — a core builder of the Vue, Nuxt, and Vite ecosystems. This is his Chinese alt account; the work itself has long been universally known in the frontend community.

82. Yun Feng @cloudwu

Author of Skynet, ltask, sproto, luaecs, and soluna, recording engineering thinking through blogs and code for decades. If you want to see how a top-tier programmer grinds on real problems across cycles, just read him.

83. Xuanwo @Xuanwo

Core maintainer of Apache OpenDAL, focused on Rust data infrastructure and deeply involved in international open-source governance. Beyond hardcore code, his practical experience in open-source collaboration and community governance is equally rare.

84. tison (Chen Zili) @tison1096

Deeply involved in Apache open-source governance and top projects like Flink, Pulsar, and ZooKeeper. If you want to understand how international open-source communities actually operate and how long-term projects collaborate, his articles are the most direct path.

85. Yun Qian (Chen Cheng) @chenchengpro

Author of UmiJS, dva, and Mako, who in the last couple of years has dived deep into AI coding and next-generation developer tools. He has both deep frontend engineering foundations and the willingness to roll up his sleeves and build new tools himself.

86. Vonng (Feng Ruohang) @RonVonng

Creator of Pigsty, grinding hard on PostgreSQL, observability, and database engineering. Extremely dense content, sharp opinions — people working on databases and foundational architecture will find it deeply satisfying reading.

87. mk2.js @fengmk2

Egg.js, Koa, cnpm… across China’s Node.js toolchain, his fingerprints are everywhere. If you’ve ever written Node, you’ve probably already used wheels he built.

88. Ka Bi Ka Bi @jakevin7

Apache Committer, spanning big data infrastructure and Agent engineering practice. He has both thoroughly absorbed traditional data systems and is on the frontlines tracking the new generation of AI engineering — this hybrid background carries real value.

89. Ruifeng @liruifengv

Maintainer of Astro, also contributing to Starlight and related ecosystem documentation. A good follow for those interested in the evolution of modern web toolchains, open-source documentation engineering, and international open-source community collaboration.

90. yetone @yetone

Author of popular projects like avante.nvim and NextAI Translator, exceptionally skilled at shaping cutting-edge model capabilities into ergonomic developer tools. Code, product, and real pain points are tightly interlocked — a quintessential person of action.

91. DIYgod @DIYgod

Author of RSSHub and Folo. In an era of algorithmic feeding, he’s still grinding with his team on open internet information retrieval and free distribution.

92. Zihua @luinlee

Core author of ioredis and Medis — a low-key powerhouse in the Chinese open-source engineering community. If you work with Node.js or Redis on a daily basis, you’ve basically crossed paths with his work.

93. wong2 @wong2__

A prolific open-source AI application developer, ships code extremely fast, and has sharp product instincts. When large models unlock new capabilities, seeing how he turns them into useful little products is itself an inspiration.

7. Programming & Developer Tools

This group spans a wide range: Linux, Rust, frontend, security, community, and desktop tools. The common thread is singular — no vague talk about programmer virtue, everything is proven by code that was actually written and maintained for real.

94. Tw93 @HiTw93

Author of popular open-source projects like Mole and Pake, frequently laying out product design and engineering trade-offs. Beyond the code, he has strong opinions on detail refinement, aesthetics, and productivity tools.

95. Andy Stewart @manateelazycat

Long-term practitioner in Linux, Deepin, Emacs, and desktop system development, publicly maintaining multiple open-source projects. His shares mostly come from real development and system maintenance experience — a good follow for readers interested in low-level engineering and desktop operating systems.

96. Tualatrix @tualatrix

From early Ubuntu Tweak to today’s multiple Apple-ecosystem indie works, he’s maintained a coding and product delivery rhythm for nearly twenty years. In him, you can see how an indie developer thrives across platforms and across cycles.

97. yihong0618 @yihong0618

A prolific open-source author, maintaining popular projects like bilingual_book_maker, xiaogpt, running_page, and more. He never puts on airs writing code — often a genuinely useful tool grows directly out of a real pain point from daily life.

98. Guo Yu @turingou

Fully committed to Agent and automation product development, documenting his new entrepreneurial chapter through code and product. You can watch technology iterate rapidly, and see how a former senior big-tech engineer re-enters the market.

99. Livid @Livid

Founder of V2EX, who for over a decade has kept an independent developer community and its underlying technical infrastructure running steadily. His restraint in product design and strength in community governance need no concepts to prove themselves.

100. Barret Li Jing @Barret_China

Has built up over a decade of technical blogging, focused on full-stack engineering, architecture evolution, and technical team management. His long-form posts are systematic and deep — worth sitting down and reading through carefully.

101. Xiang Ma @xicilion

Founder of Xici Hutong and fibjs, with extremely deep foundations in systems programming, asynchronous execution mechanisms, and engineering architecture. The content is quite hardcore — developers working on performance optimization and runtime mechanics will find him very satisfying.

102. Kai @real_kai42

Author of Qwerty Learner, which combines vocabulary memorization with keyboard typing practice, creating a tool project with wide attention in the open-source community. A good case study in how a developer starts from a personal concrete need, continuously iterates, and operates an open-source product.

103. Jason Young @Jason_Young1231

Author of CC Switch, exceptionally good at identifying developer pain points and quickly delivering tools. AI coding tools change generations extremely fast — what he covers are the concrete problems developers actually face when writing code every day.

104. AlexZ 🦀 @blackanger

A rare hands-on practitioner and systematic writer in the Chinese Rust community. Whether you’re getting started with Rust or want to see how it navigates pitfalls in large-scale real-world engineering, keep a close eye on him.

105. Randy Lu @randyloop

Interaction design in one hand, full-stack development in the other, documenting a Product Engineer’s workflow year after year. If you want to write beautiful code but absolutely refuse to compromise on product experience, his posts will be deeply rewarding.

106. lencx @lencx_

Author of Rust/Tauri tools like ChatGPT Desktop, Noi, Minke, and more. Ships extremely fast, committed to open source — anyone working on desktop AI applications and cross-platform development can dig up plenty of good stuff from him.

107. Huli @hulitw

Year after year breaks down web security, network protocols, and supply-chain attacks in Traditional Chinese. He can explain deeply convoluted underlying attack and defense mechanisms with crystal clarity — a treasure author for developers shoring up security blind spots.

108. Chen Da Huang @realchendahuang

Closely tracks AI development tools and engineering frontiers, skilled at distilling new product changes into a few well-placed short takes. Use him as a regular tech radar — when something catches your eye, follow the leads he provides to the original project.

8. Investment, Industry & Long-Form Writing

Technology doesn’t happen in a vacuum. Compute, capital, supply chains, organizations, and social narratives all loop back to determine how far a product can go. This group helps you fill in the other half of the puzzle beyond pure technology.

109. Hong Hao @HAOHONG_CFA

Macro data, signature reports, and cycle models are his hallmarks. The point of reading him is to learn that data framework and deductive logic — not to get a definitive answer on whether markets will rise or fall.

110. Bobo OC @bboczeng

Grinds hard on US tech company financials and fundamentals. If you want to understand how product popularity gradually reflects into revenue, profit, and valuation, his continuous earnings breakdowns are very solid.

111. Macro_Lin @LinQingV

Closely tracks the global semiconductor supply chain and capital operations, able to discuss both technology and finance in depth. Very handy for tracking compute, chips, and upstream/downstream industry trends.

112. Silicon Valley Wang Chuan @Svwang1

Likes to discuss investing and business by putting technology, energy, and historical cycles on the same plate. The breadth of perspective is enormous — excellent for opening your mind and stretching the time horizon of your thinking.

113. Star @starzq

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