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小宇宙 / Apple Podcasts / Spotify → 「离线时间」This is the first episode of「离线时间」Stolen Chat. Our guest is Weng Wei — known on Zhihu as "Gamer Weng Wei," a top food writer whose analytics ironically categorize him under politics and economics. His tagline: "A CTO who doesn't understand food isn't a good keyboard warrior."
He graduated from NUS Computer Science in 2006, rose from junior developer to architect to CTO, helped take a cross-border e-commerce company from Series A to a Nasdaq listing, then became regional CTO for Southeast Asia at an A-share listed company. After two decades in pure tech, he went back for a master's in economics.
Now in his forties, he says this is his absolute peak — in learning speed, output, and productivity. Because of AI.
From managing dozens to paying a subscription
As CTO, Weng Wei used to manage teams of several dozen — frontend, backend, ops, QA, product. Now he does the same work alone with AI.
"I didn't write code before, and I don't now. Before I told human engineers what to build, now I tell AI. The management work is identical — discussing technical architecture, product strategy, business positioning. Sometimes when AI can't get a critical piece right, I still jump in myself. Exactly like being CTO. The difference? Before I needed extremely expensive headcount. Now I pay a subscription fee."
The faster AI gets, the slower he goes
After a year with AI, Weng Wei made a counterintuitive choice — to slow down.
"AI's implementation speed is too fast, I can't even digest it all. Sometimes I build this and that without thinking — but what's the point? Should I even be doing this? I haven't thought it through."
He prefers typing over voice input because typing forces deliberation. "Efficiency has already exceeded what my brain can process. I need to make sure I'm still thinking."
He saw a post that morning: in the AI era, as long as you learn slowly enough, there's a lot you don't need to learn at all. He agreed. Over the past year, he avoided MCP and several other hot concepts. Six months later, the industry started turning against MCP too.
What is taste? Start with food
I asked him — everyone says taste matters most in the AI era. How do you define it?
"Food obviously requires taste. How do you build it? First, you eat a lot. If you haven't tasted flavors that exist, how can you judge?"
Same with technology. The book that influenced him most was "The Design and Evolution of C++" — a language he never used professionally. "That book traces every problem C++ faced at each stage and how they solved it. Once I saw the full arc, technology became three-dimensional to me."
Then he gave a cooking example: why do you add cold water three times when boiling dumplings? Because old wood-fire stoves couldn't quickly lower temperature, so you added water. With a gas stove, just turn down the flame.
"Most people just memorize recipes. You need to think about why a technique exists, abstract the underlying principle, then reconstruct the method for a better result."
He later learned this concept had a name — first principles. "I only found out after Elon Musk made it famous. Kind of funny."
This AI revolution will exceed all industrial revolutions combined
Weng Wei isn't an AI scientist, but he sees things differently through an economics lens.
"Keynes predicted roughly 100 years ago that in a century, society would reach a point of surplus productivity where people wouldn't need to work. I think that prediction is coming true."
"Many say old jobs disappear but new ones appear with every technological shift. I think that's wishful inertia. This time is genuinely different."
Why? "It's a demand problem. Past productivity gains created new desires, which created new jobs. But now supply is oversaturated and demand is declining. Japan's low-desire society, China's 'lying flat,' anti-consumerism — demand is falling. Supply up, demand down, jobs disappear."
The future's problem isn't abundance or scarcity — it's inequality.
Singapore should be a small but complete sparrow
On Singapore's role in the AI era, his view was clear:
"Singapore's success, honestly, is mostly thanks to its peers underperforming. It's not exceptionally strong anywhere — it's just lucky enough to avoid internal dysfunction."
Two critical judgments about the future: First, Singapore can't cling dogmatically to Lee Kuan Yew's playbook. Second, Singapore's existential question is whether it can continue not picking sides as geopolitics intensifies.
On AI industry strategy, he believes Singapore should go deep on the application layer with a full-stack approach — education, talent, industry development, financing, policy. "Singapore can't be big, but it can be strong. Can't build foundation models? Fine — do more applications."
He's also bullish on nuclear energy: "AI is ultimately an energy problem. Singapore should boldly pursue nuclear — if you can't build on the island, negotiate with Malaysia."
这是「离线时间」第一期对话。嘉宾是翁伟。
知乎 ID「玩家翁伟」,美食话题优秀答主,但后台数据把他归到了时政经济类——他自嘲是个键盘侠。他的 slogan 是:不懂美食的 CTO 不是好的键盘侠。
06 年新加坡国立大学计算机系毕业,从一线程序员做到架构师、技术总监、CTO,帮一家跨境电商从 A 轮做到并购上市,后来又担任 A 股上市企业的东南亚区域 CTO。做了十几二十年纯技术之后,他去念了经济学硕士。
现在四十几岁,他说这是他人生中学习速度最快、产出效率最高的巅峰。因为有了 AI。
以前管几十人,现在付个订阅费
翁伟以前做 CTO,管大几十人的技术团队——前端、后端、运维、QA、产品,都得管。现在他一个人用 AI 做同样的事。
"以前我不需要自己写代码,现在我也不用。以前我叫真人程序员帮我写,现在我叫 AI 帮我写。我做技术管理的事情一点都没变——跟 AI 讨论技术方案、产品方案、商业定位,定技术架构。有时候 AI 写不出来的关键代码,我还得自己下手。跟我之前当 CTO 一模一样。区别在哪?以前我需要负担非常高昂的人力成本,现在我付一下 AI 的 subscription fee 就可以了。"
AI 越快,他反而越慢
用了一年 AI 之后,翁伟做了一个反直觉的选择——放慢速度。
"AI 的实现速度太快了,我自己都消化不过来。有时候一不留神,这个也做那个也做,但那个东西有什么用?要不要做?我自己没想清楚。"
他说自己更喜欢打字而不是语音输入,因为打字可以思考、斟酌字眼。"效率已经超过我人脑能消化的了,我需要确保自己有思考的过程。"
今天早上他还刷到一个帖子:在 AI 时代,只要你学得够慢,很多东西你就不用学了。他深以为然。过去一年,他避开了 MCP 等多个热门技术概念。半年后,行业风向开始转了——开始有人批评 MCP。
品味是什么?先从美食说起
我问他,大家都说 AI 时代最重要的是品味,你怎么理解这个词?
"美食你肯定需要品味。那怎么建立品味?首先你要吃得够多。很多存在的味道你连吃都没吃过,你怎么品?"
技术也一样。他说对自己影响最大的一本书,叫《C++ 的设计与演变》——但他工作中从来没用过 C++。
"那本书把 C++ 发展各阶段面临的实际问题、当时怎么解决、怎么改变,一步一步讲清楚。当我看清这个脉络,很多技术的东西在我面前就变成立体的了。"
然后他讲了一个例子:煮饺子为什么要三点水?因为以前用柴火灶,水温没法快速降温,所以要加水。换了煤气炉之后,直接关火就行了。
"很多人只会背食谱,但你需要思考它为什么有这样的做法,抽象出背后的规律,然后你可以把原来的方式重构,达到更好的效果。"
他后来才知道,这个东西叫第一性原理。"马斯克火了我才知道的,挺搞笑。"
这次 AI 革命,会超过所有工业革命的总和
翁伟不是 AI scientist,但他从经济学的视角看到了一些不同的东西。
"凯恩斯差不多 100 年前就预言过,100 年后的社会会到一个生产力过剩、大家不需要工作的社会。我觉得这个预言正在兑现。"
"很多人说每次技术变革旧工作没了,新岗位会出现。我觉得这是一厢情愿的惯性思维。这次真的不一样。"
为什么?"主要是需求的问题。过去生产力发展后会产生新需求,所以有新工作。但现在很多社会供给过剩、需求不足。日本的低欲望社会,中国的躺平,反消费主义——需求在下降。供给上升、需求下降,工作自然就没了。"
他说未来社会的问题不是多寡,而是不均。
新加坡要做一只五脏俱全的顽强麻雀
聊到新加坡在 AI 时代的角色,翁伟的判断很清晰。
"新加坡能发展起来,说实话,全靠同行衬托。它没有特别厉害的地方,只是比较幸运没有陷入内耗。"
关于未来,他提了两个关键判断。第一,不能搞"两个凡是"。第二,新加坡的生死问题是:还能不能继续不选边站。
在 AI 产业上,他认为新加坡应该做强应用层,做全链条——教育、人才、行业发展、融资、政策支持。"新加坡做不大,但可以做强。搞大模型本身搞不了,那就多做应用。"
他还看好核能。"AI 最终是个能源问题。新加坡应该放心大胆去搞核能,岛上建不了就跟马来西亚谈。"
This is an episode of「离线时间」Stolen Chat. If you're building in AI and thinking about going global, I'd love to hear from you.