William Cheong

Software Architect, Aspiring Entrepreneur & Dad who codes, I bring people together designing experience and create values

[William Cheong @divineforge]

Here's a list of my tweets on Sample Projects and Demo Codes that I have found online.
#handpicked #code #projects

[William Cheong @divineforge]

I have tried doing something similar during the MSc. Software Engineering final project, that tooks me months in environment generation algorithm and via Unity, just this one is way more polished than I do. thanks to many more human behind it that make my day.

[William Cheong @divineforge]

playing with coding in the antigravity, it's kinda delighting to see what Ai is capable of doing than what I have tried like more than a decade to complete a playable version.

[皓樂芒 @howlemont]

微软，总算出了个好东西。

开发了一款工具，

可以将几乎任何格式pdfs，word，docs，excel，PowerPoint，Audio，YouTube 网址

转换为Markdown文件，
众所周知Markdown 是AI 大语言模型最青睐的格式。

没有自定义解析器。没有损坏的布局。没有混乱的文本。

只是干净、结构化的标记，

只需一次安装

https://t.co/gyZGOdceG7

[阿川 | AI thinking @AI_jacksaku]

微软终于开源了VibeVoice。

24K+ stars，不是玩具，是生产级语音AI。

支持实时语音克隆、情感控制、多语言切换。延迟低到可以实时对话，质量高到难以分辨真假。

这意味什么？

语音交互的门槛，归零了。

以前做���音���手要调ASR、TTS、NLP三件套，现在一个模型全搞定。创业者可以用VibeVoice在几小时内搭建自己的"Her"。

但这里有个问题：当语音克隆变得如此简单，声纹认证还安全吗？

你的声音，正在变成可复制的数据。

技术越开放，风险越隐蔽。https://t.co/CIImwp4wZO

[MIT CSAIL @MIT_CSAIL]

A prompt you can use in Claude to help build & launch apps, v/@milesdeutscher.

[Rohan Paul @rohanpaul_ai]

Claude seems to be fixing a super annoying developer problem.

Anthropic announced a research preview feature called Auto Mode for Claude Code, expected to roll out by March 12, 2026.

The idea is simple: let Claude automatically handle permission prompts during coding so developers don’t have to constantly approve every action.

Sstops those annoying permission prompts during long coding sessions.

Before this, you had to use `--dangerously-skip-permissions` to work without interruptions.

That method worked fine but took away all your safety nets. This new auto mode gives us a smarter option.

Claude will take care of the specific permission choices on its own while still blocking threats like prompt injections.

You can finally let long tasks run without watching your screen the whole time.

Since it is still a research preview, you should run it inside isolated setups like sandboxes or containers for safety.

Expect a small jump in token usage and delay, because the model needs extra time to process the security checks.

Once available, you just type `claude --enable-auto-mode` to start.

If you manage a team and need people to manually approve actions, you can restrict this feature using Mobile Device Management tools like Jamf and Intune or through configuration files.

[William Cheong @divineforge]

本身是认同的。
CLI 今天确实是非常强大

[Orange AI @oran_ge]

今天 HackerNews 上有一篇很有趣的文章
《MCP 已死，CLI 永生》
它断言 MCP 已经在走向衰亡。
理由是：大模型并不需要特殊的协议
最好的工具总是既能为人所用，又能被机器高效处理的。
而 CLI 就是那一个很好的工具。
如果现在的轮子就很好用，我们并不需要再次发明轮子
https://t.co/DIS7X1wcel

[William Cheong @divineforge]

https://t.co/uLKsN3Bn4d; the workplace observed. and the machine helps me to reveal it better about the life surrounded by machine and computers

[William Cheong @divineforge]

I follow the link and trace until to the original version that was forked.

[DinoDeer @xDinoDeer]

https://t.co/2PVfHwfsHj

[Andy Stewart @manateelazycat]

讲一个北京的故事

前年去北京，北京几个哥们喝酒聊到了娃

A：海淀真的卷啊，我的娃每周凌晨睡觉，每周末5个补习班，真的觉得太辛苦了

我：为什么不退掉补习班？

A: 我就在体制内工作，没有学历，别人看不起你

B：我就不上补习班，我现在就拼命赚钱，北京两套房，云南一套房，不鸡娃，等娃以后出社会了，帮衬她一点

我全程听着没说话，A和B两个哥们��头问我，我怎样养娃的，我说我和B这位大哥差不多

我是现代苏牧，放养选手，我的娃周末只上一个画画课，她喜欢，其他补习班一概不上，甚至家长会怼班主任：时光倒流一万年，我也不上补习班！班主任：你是谁的家长？我：我是xxx的爸爸！！！

我经常给娃讲，你从小到大一个补习班没上，你的成绩中上等，那些经常第一的7x360天没休息，到底他是学霸，还是你是学霸？

这是我经常给娃说的：
1. 学历和考分���重要：学习很重要，不要把精力都浪费在上学考分上，正常学习就可以了，你长大出社会的时候，那才是你真正开始学习投入能量的时候，不要天天考分，以后出社会需要学习的时候厌学

2. 世界上什么最珍贵？家人的陪伴，自己的好奇心，旅游路上的风景，旅游过程中遇到的小动物和不同种族的人文风情，那些才重要。那才是人来到世界上应该有的痕迹

3. 你身上有重要的东西：只是现在教育体制不考试而已，以后长大定有大用：好奇心、观察力、冷笑话幽默感、人缘好、记忆力强、野外抗饿和生存能力、画画可以画6个小时、读书可以读几天的专注力......这些都是爸爸教给你出社会的大技能，好好保留

[赴野 @duanhjlt]

今年40了，从弱冠到而立再到不惑，更多的是不确定��无奈和焦虑吧
1/

[赴野 @duanhjlt]

你长期拖延，是因为大脑缺“微小胜利”

[Heath Ahrens @heathahrens]

Part 2: The Two-Factory Model

Jensen's insight that changed how I see every business: "Every company in the future will have two factories."

Factory 1: Your actual product. Factory 2: The AI that powers it

Tesla gets this. They build cars and build AI brains for them...

[Calvin French-Owen @calvinfo]

Some reflections: https://t.co/3UQQuFy0sl

[William Cheong @divineforge]

Gotta be my new favourite font too!

[Steven Tey @steventey]

Good news: We just open-sourced Geist, our official @vercel font → https://t.co/grG0V6QDbv

This is gonna be my new favorite font for all my future open-source projects 🤩

▲ ~/ npm i geist

[Bytebytego @bytebytego]

Do you believe that Google, Meta, Uber, and Airbnb put almost all of their code in one repository?

This practice is called a monorepo.

Monorepo vs. Microrepo. Which is the best? Why do different companies choose different options?

Monorepo isn't new; Linux and Windows were both created using Monorepo. To improve scalability and build speed, Google developed its internal dedicated toolchain to scale it faster and strict coding quality standards to keep it consistent.

Amazon and Netflix are major ambassadors of the Microservice philosophy. This approach naturally separates the service code into separate repositories. It scales faster but can lead to governance pain points later on.

Within Monorepo, each service is a folder, and every folder has a BUILD config and OWNERS permission control. Every service member is responsible for their own folder.

On the other hand, in Microrepo, each service is responsible for its repository, with the build config and permissions typically set for the entire repository.

In Monorepo, dependencies are shared across the entire codebase regardless of your business, so when there's a version upgrade, every codebase upgrades their version.

In Microrepo, dependencies are controlled within each repository. Businesses choose when to upgrade their versions based on their own schedules.

Monorepo has a standard for check-ins. Google's code review process is famously known for setting a high bar, ensuring a coherent quality standard for Monorepo, regardless of the business.

Microrepo can either set their own standard or adopt a shared standard by incorporating best practices. It can scale faster for business, but the code quality might be a bit different.

Google engineers built Bazel, and Meta built Buck. There are other open-source tools available, including Nix, Lerna, and others.

Over the years, Microrepo has had more supported tools, including Maven and Gradle for Java, NPM for NodeJS, and CMake for C/C++, among others.

Over to you: Which option do you think is better? Which code repository strategy does your company use?

–
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[Bytebytego @bytebytego]

7 must-know strategies to scale your database.

1 - Indexing:
Check the query patterns of your application and create the right indexes.

2 - Materialized Views:
Pre-compute complex query results and store them for faster access.

3 - Denormalization:
Reduce complex joins to improve query performance.

4 - Vertical Scaling
Boost your database server by adding more CPU, RAM, or storage.

5 - Caching
Store frequently accessed data in a faster storage layer to reduce database load.

6 - Replication
Create replicas of your primary database on different servers for scaling the reads.

7 - Sharding
Split your database tables into smaller pieces and spread them across servers. Used for scaling the writes as well as the reads.

Over to you: What other strategies do you use for scaling your databases?

–
Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): https://t.co/FIzCeaWsZV

[Alex Xu @alexxubyte]

Netflix's Tech Stack.

This post is based on research from many Netflix engineering blogs and open-source projects. If you come across any inaccuracies, please feel free to inform us.

Mobile and web: Netflix has adopted Swift and Kotlin to build native mobile apps. For its web application, it uses React.

Frontend/server communication: GraphQL.

Backend services: Netflix relies on ZUUL, Eureka, the Spring Boot framework, and other technologies.

Databases: Netflix utilizes EV cache, Cassandra, CockroachDB, and other databases.

Messaging/streaming: Netflix employs Apache Kafka and Fink for messaging and streaming purposes.

Video storage: Netflix uses S3 and Open Connect for video storage.

Data processing: Netflix utilizes Flink and Spark for data processing, which is then visualized using Tableau. Redshift is used for processing structured data warehouse information.

CI/CD: Netflix employs various tools such as JIRA, Confluence, PagerDuty, Jenkins, Gradle, Chaos Monkey, Spinnaker, Altas, and more for CI/CD processes.

[William Cheong @divineforge]

為什麼很多人對生活越來越無感？(中英字幕) https://t.co/7V7out6DLK via @YouTube

[William Cheong @divineforge]

after a while of linux desktop hunting, I realise, maybe RHEL, Fedora for workplace, or enterprise setup. For personal use, home environment, now I'm sticking with Ubuntu, the KDE Plasma desktop, the... Kubuntu.