Podcasts · Video · Long-form

Take one real question all the way—and help the conversation travel farther.

Yuzheng Sun in conversation with Ben Gilbert and David Rosenthal of Acquired
With Ben Gilbert and David Rosenthal of Acquired · Significance Summit

You set the question. I’ll bring first-hand experience and evidence, and we’ll follow the question wherever it leads. We can use your usual format; my team can also help with editing, clips, and co-publishing.

See the collaboration casesDownload the guest kit

Research to practice

Cornell PhD · Amazon · Meta · Tencent · Statsig

Long-form experience

200+ public conversations · 23 verified guest appearances

Cross-platform

YouTube · Bilibili · Xiaohongshu · 400K+ followers

Production-ready

Remote or Seattle · editing and co-publishing available

TWO COLLABORATIONS · TWO KINDS OF PROOF

Good content should hold on its own—and reward further investment.

The Koji episode shows what the conversation can do with a simple remote setup and the host’s own channels. The Tulong episode shows what can happen when both teams edit, distribute, and build around the same recording.

Crossing with Koji × Yuzheng Sun

CASE 01 · THE CONTENT HOLDS

A remote conversation crossed long-form audio and three video platforms

Crossing with Koji × Yuzheng Sun

67K

Xiaoyuzhou plays

Show Top 2

12K

Douyin likes

Account all-time high

8,343

Xiaohongshu saves

Account annual high

6,502

WeChat Channels shares

Cross-platform sharing

A 63-minute remote recording became one of Crossing’s two most-played episodes. Its clips set Koji’s all-time Douyin like record and annual Xiaohongshu save record. Koji’s team handled the production and publishing; my accounts did not co-publish, so the result is unusually clean evidence of the topic and conversation itself.

Also: 132 Xiaoyuzhou comments; 4,709 Xiaohongshu likes; 8,582 Douyin saves and 1,476 shares.

“A genuinely useful episode. I’m moving from ChatGPT to Codex and building up my context.” — Xiaoyuzhou listener
Listen on Xiaoyuzhou
View platform screenshots (4)
Crossing episode listed among the most popular with 67K plays and 132 comments
Xiaoyuzhou · 67K plays · 132 commentsOpen full screenshot
Koji clip on Xiaohongshu with 4,709 likes and 8,343 saves
Xiaohongshu · 4,709 likes · 8,343 savesOpen full screenshot
Koji clip on Douyin with 12K likes, 8,582 saves and 1,476 shares
Douyin · 12K likes · account recordOpen full screenshot
Koji clip on WeChat Channels with 6,502 shares
WeChat Channels · 6,502 sharesOpen full screenshot
Yuzheng × Yang Ying (Tulong)

CASE 02 · BOTH SIDES AMPLIFY

Two teams made different cuts—and introduced the guest to new audiences

Yuzheng × Yang Ying (Tulong)

58.7K

Xiaohongshu likes

Co-published

59.6K

Xiaohongshu saves

More saves than likes

110K+

YouTube views

New viewers discovered Tulong

108K+

Bilibili views

Long-form reach

Tulong’s team kept the voice of her show. Our team made a second long-form version and clips for Xiaohongshu, YouTube, Bilibili, and the Superlinear community. The collaboration produced breakout numbers and brought Tulong to viewers who had never encountered her before.

Also: 11.3K Xiaohongshu shares and 1,088 comments; 3.6K YouTube likes and 481 comments; 8,026 Bilibili saves.

“I hadn’t known her before, but she’s incredibly cool. I hope they talk every year so we can see how her thinking changes.” — YouTube viewer (translated)
Watch the YouTube cut and comments
Verify the latest Xiaohongshu result (1 screenshot)
Yuzheng and Tulong co-created Xiaohongshu video with 58.7K likes, 59.6K saves, 11.3K shares and 1,088 comments
Our cut · 58.7K likes · 59.6K saves · 11.3K shares · 1,088 commentsOpen full screenshot

Counts come from public platform pages and screenshots captured in July 2026. Platforms use different counting methods.

WHERE AN EPISODE COULD BEGIN

Four questions that can carry a full conversation.

Choose the one your audience is already living through. We can take it from a sharp opening claim into mechanisms, first-hand cases, disagreement, and practical consequences.

01

When AI makes ‘being able to make’ cheap, why does a defining body of work matter more?

As acceptable first drafts multiply, the scarce parts move to choosing the problem, setting the standard, exercising craft, remaining recognizably responsible, and staying with the work. A defining work also compounds context, trust, and the next opportunity.

MAKE WHAT LASTS · creator work · real projects

02

Will AI eliminate fake work—or make it far easier to manufacture?

AI can remove the interface tax between work and results. It can also produce reports, meeting notes, and visible activity at almost no cost. What should an organization measure when busyness becomes abundant?

Organizational design · incentives · enterprise AI

03

What actually makes someone AI-native?

Tool fluency is the visible part. The deeper shift is to start from the result, recompute the whole workflow, build compounding context with AI, and remain accountable for the outcome.

AI Builders · 700+ community projects · enterprise programs

04

How does a company know when its judgment is wrong?

Data, experiments, and professional process can correct a mistake—or fortify it. Across Amazon, Meta, Tencent, and Statsig: when do organizations get closer to reality, and when do they merely become better at explaining themselves?

Economics · data science · big tech and startups

Other directions include the public AI calls I made before GPT-4, experimentation, creator businesses, China–U.S. technology, and the design of AI education and community. One real question is stronger than a complete tour.

WHERE THE VIEW COMES FROM

I have met the same questions from several sides.

01

Research, products, organizations, and early-stage work

A Cornell Economics PhD led to work at Amazon, Meta, Tencent, and the early Statsig team. At Tencent I led a 30-person Data & AI team and received the highest performance rating in two consecutive cycles.

Mechanisms · product judgment · organizational reality

02

Keep the original judgment—and the corrections—public

In 2021 I described the ceiling of the dominant AI paradigm. In February 2023, before GPT-4, I argued that ChatGPT had begun to break it—and reasoned forward to cheaper inference, tool use, persistent memory, and AI-native systems. The original probabilities and later corrections remain public.

A dated, public chain of reasoning

03

Put the ideas inside a system I am responsible for

At Superlinear, the ideas meet courses, a 20,000+ member community, 700+ real projects, enterprise programs, and more than 200 public conversations. They have to remain useful after the talk is over.

Superlinear Academy · real projects · enterprise work

SELECTED BY OTHER SHOWS

Invited across AI, technology, organizations, careers, and creator businesses.

The list below emphasizes recognizable shows and repeat invitations. A complete 23-episode Xiaoyuzhou archive remains available for producers who want to inspect the full record.

Crossing with Koji

Remote long-form · show Top 2

Tulong Dashihua

Co-produced · cross-platform breakout

Silicon Valley 101

AI Agent roundtable

INDIGO TALK

Two invitations

The Build Log

Two invitations

What’s Next

Pre-GPT-4 AI discussion · 2023

PROGRAM INVITATIONS

If there is a question worth taking all the way, send it over.

Send the show or channel, the question you most want to pursue, and a rough format and timing. If I have something genuinely new to add, we can set a time and prepare around the show.

Discuss an episode
yz@superlinear.academy

Business contact: Miao (喵老师) | WeChat: FM13870617

01

The host sets the frame.

You choose the questions, pacing, title, and final edit. We can align on direction before recording; I do not require pre-approval of questions or the final cut.

02

Prepare around one or two real questions.

I can bring primary sources, data, first-hand cases, and the strongest counterargument I can find—not scripted answers.

03

Disagreement can stay; a judgment can change.

I will state the view clearly and say what evidence could overturn it. The best conversations make me re-check—and sometimes change—how I think.

04

Facts deserve care.

Before release, I can help check names, dates, quotations, and data. The editorial conclusion remains yours.

For a jointly published episode, we can agree in advance on the primary cut, editing responsibility, clip rights, and release timing.

RECORDING DETAILS

Production details, without ceremony.

Languages

Mandarin or English

Format

Remote, or in person in Seattle

Length

Usually 60–120 minutes; adaptable to the show

Based in

Seattle · Pacific Time

COMPLETE ARCHIVE

Open all 23 verified guest appearances

The full Xiaoyuzhou archive is preserved here for producers who want to check topics, formats, and earlier work.

屠龙大实话

59. 线性思维害死人？和康奈尔大学经济学博士课代表立正扒一扒这个思维中的隐形巨坑

十字路口 Crossing

高手怎么用 AI？普通人怎么学 AI？投资人如何投 AI？｜对谈课代表立正

The Build Log

#9 Is power at work an illusion? Borrowed authority and real influence

Grad Lounge 不止学术

118. From the ivory tower to real capability: building personal value in the AI era

Talk to JANE｜对话身边的人

拆解职场进阶的世纪谎言｜Waking Up at the End of the Ladder

AI炼金术

课代表立正：AI 课卖 2000 刀，偏偏坚持古法手搓

The Wanderers 流浪者

从焦虑到上手：白领 / 投资者的 AI 实战第一课【串台课代表立正】

INDIGO TALK

Quit ChatGPT to become an AI orchestrator / AI as a second Renaissance · EP46

人民公园说AI

腾讯“血脉觉醒”：马化腾朋友圈背后，小龙虾和大模型我都要！

创见｜对话顶级创投大脑

#031 关于 OpenClaw 被封杀以及我们为什么不建议普通人养龙虾？

牛油果烤面包

#148. 我们为什么 AI 焦虑，我们又该怎么脚踏实地

在路上｜ON THE ROAD

Vol.74｜大厂的收入是幻象，你的焦虑也是

破壁圆桌

EP14：对话课代表立正：AI时代下，后悔没早点离开职场

小火车商业进化论

课代表立正：知识内容大 V 分享 6 个你不知道的涨粉秘诀

StellaxAmy·自定义

EP77 Startup 选择、AI Evals 怎么做、Data Science 未来

佐治亚小帅｜北美华人故事访谈

S7E10 AI时代的新毕业生怎么办｜课代表立正

Panel

硅谷101

E195 · From tool to partner: seven experienced AI agent users

The Build Log

#1 课代表立正：打开第四面墙，走进课代表的世界

INDIGO TALK

对谈课代表立正：AI 时代生存指南 · EP20

王路在隐身

康奈尔博士、数据科学家、玄学、阿毗达磨

商业 WHY 酱

S3E03 · Before asking how to profit, ask the basic questions about ChatGPT

Panel

What’s Next｜科技早知道

How should we respond to ChatGPT? Highlights from a closed-door market discussion

随机漫谈 Random Talk

跨境电商都是怎么赚钱的？

HOST KIT

A producer can build the introduction from this page.

Use whichever bio length fits the show. The facts and links are here for verification, not as required talking points.

Download the six-page Chinese guest kitYuzheng Sun

1280 × 1280 headshot

Download headshot

Short bio

Yuzheng Sun (课代表立正) has a PhD in Economics from Cornell and is the founder of Superlinear Academy. He was an economist at Amazon, a data scientist at Meta, Vice Director of Data & AI at Tencent IEG, and an early member of Statsig, which was later acquired by OpenAI. His work asks what capabilities and works matter more when AI makes execution cheaper.

View full bio

Yuzheng Sun (课代表立正) has a PhD in Economics from Cornell and is a founder, operator, and author based in Seattle. He was an economist at Amazon, a data scientist at Meta, Vice Director of Data & AI at Tencent IEG—where he led a 30-person team and received the highest performance rating in two consecutive cycles—and an early member of Statsig, which was later acquired by OpenAI. He founded Superlinear Academy, the parent institution for its free community, AI Builders, and Stay Superlinear. His defining idea is MAKE WHAT LASTS. As of August 2026, he has taught 3,000+ paying learners, held 200+ public conversations with researchers, founders, and operators, and built a free community of 20,000+ members with 700+ shared real-world projects. He is co-author of Growth Data Analytics Playbook and author of 《真本事》.

One line for the introduction

MAKE WHAT LASTS.

Public facts & source links

Dated public AI calls200+ published conversationsAI Builders · 3,000+ paying learnersStay Superlinear membership
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