Chiahao Lin (Hao)

Otter & JavaScript & Rust Lover - 🇨🇦 🇹🇼

[Shadow Nick @doublenickk]

Anthropic shipped 125 settings for Claude

The official docs cover 40

One developer found the other 85 and his API bill dropped from $340 to $87

- not by using a cheaper model
- not by writing shorter prompts

just by moving one line in a config file to the right place

> memory scoped per project → past clients never bleed into new work
> Extended Thinking on Light by default → 18–25% fewer Opus tokens in week one
> cache_control moved to the right line → the fix that turned a $340 bill into $87
> plugins and MCP servers toggled off when idle → saved 25–40K tokens per session
> per-project model override → Haiku for docs, Sonnet for infra, Opus only where it matters

most Claude users are running a $100/month tool at 30% of its actual capability

[Thariq @trq212]

a prompt I've been using a lot recently:

implement <SPEC> and while you do, keep a running implementation-notes.html file (or markdown) with decisions you had to make weren't in the spec, things you had to change, tradeoffs you had to make or anything else I should know

[Garry Tan @garrytan]

https://t.co/EVPCod6rxu

[Boris Cherny @bcherny]

Mistakes happen. As a team, the important thing is to recognize it’s never an individuals’s fault — it’s the process, the culture, or the infra.

In this case, there was a manual deploy step that should have been better automated. Our team has made a few improvements to the automation for next time, a couple more on the way.

[宝玉 @dotey]

看鸭哥写的：《AI 工程的真实代价：从 Claude Code 泄露源码看新模型接入的工程现实》
https://t.co/Cz5XBMXnCk

里面提到了 Anthropic 在 Claude Code 里埋了三层反蒸馏机制，专门防竞争对手用 API 输出来训练自己的模型。泄露的源码把这套系统完整暴露了出来。

第一层：往输出里掺假。API 返回结果时，服务端会混入一些虚假的工具调用数据。正常用户完全不受影响，服务端会帮你过滤掉。但如果有人批量抓取 API 输出去训练模型，这些假数据会一起被吃进训练集，污染模型质量。

第二层：把推理过程藏起来。Claude 在工具调用之间会产生中间推理文本，比如"我先读这个文件，再检查语法"。这些细节对蒸馏训练价值很高，因为它暴露了模型怎么思考。这一层把中间文本替换为一句摘要加密签名，下一轮对话时客户端拿签名换回原文。外部观察者只能看到摘要，完整推理链拿不到。

第三层：协议隔离。Claude Code 用一种新的 JSON 协议格式跟 API 通信，带独立的版本标记，跟每周 920 万次的普通 API 请求在统计上隔离开。服务端可以对不同群体做差异化处理，也让竞争对手无法简单伪装成 Claude Code 来获取特殊待遇。附带好处是省了大约 4.5% 的输出 token。

[Xiao Tan @tvytlx]

https://t.co/i4jBHevGEi

[逆瀬川 @gyakuse]

ClaudeにComputer-useが入ったので使ってみました (動画は10倍速)。推論速度はこれからという感じですが、ちゃんとタスク完遂してくれて嬉しい気持ちがあります。
設定 > デスクトップアプリ 一般 > コンピュータ使用をONで使えます。

[Thariq @trq212]

https://t.co/45C3gKydTK

[Rimsha Bhardwaj @heyrimsha]

I accidentally discovered how to compress a month of research into 3 hours.

A founder at a YC company showed me his Claude setup. I thought he was just fast. Then I watched him build an entire go-to-market strategy for a market he'd never worked in before.

Here's exactly what he did:

First: he didn't ask Claude to "research the market."

He fed it 8 competitor landing pages, 3 earnings call transcripts, 12 customer reviews, and a Reddit thread of complaints.

Then he asked one question:

"What does every successful player in this market understand that their customers never say out loud?"

Not "summarize these." Not "analyze the competition."
The unspoken insight. The thing that takes founders 2 years of customer calls to figure out.

But the next part is what broke my brain.

He followed up with:

"Now show me the 3 assumptions this entire market is built on, and what would have to be true for each one to be wrong."

In 15 minutes he had the attack surface of an entire industry.
The blind spots. The fragile consensus. The opening nobody was talking about.

Most founders spend 6 months doing customer discovery just to find one of those.

Then he did something I've never seen before.

He asked:

"Write 5 questions a world-class investor would ask to destroy this business idea, then answer each one using only the evidence in these documents."

He spent the next 2 hours stress-testing every assumption. Every weak answer triggered a follow-up:

"What's the strongest version of this argument and where does it still break?"

By hour 3, he had a strategy deck that felt like it came from someone who'd spent a decade in the space.

The tool didn't change. The questions did.

Most people treat Claude like a faster Google.

These founders are using it like a thinking partner who has read everything and has no ego about being wrong.

The difference between 3 hours and 3 months isn't the amount of information.

It's knowing which questions actually matter.

[实践哥MinLi @MinLiBuilds]

人类能达到的满级 prompt 能力，值得学习。经常听说降维打击，这次来看看怎么用 Claude 做升维打击的，从浓缩数据里挖出隐藏的关键细节信息。

​我不小心发现了一个秘密：如何将一个月的研究工作，压缩到短短 3 小时内完成。

​在一家 YC 入选公司的创始人那里，我见识了他的 Claude 配置。起初，我以为他只是手快；直到我亲眼看着他为一个从未涉足过的领域，构建出了一套完整的进入市场GTM策略。

​以下是他的完整操作：

​第一步：他并不要求 Claude 去研究市场。​他喂给 AI 的是：8 个竞争对手的落地页、3 份财报电话会议记录、12 条客户评价，以及一整条吐槽产品的 Reddit 帖子。

​然后，他只问了一个问题：​“关于这个市场，那些成功的玩家都洞察到了哪些客户永远不会明说的潜规则？”

​不是“总结一下”，也不是“分析竞争对手”。而是“未被言说的洞察”——那种通常需要创始人打两年的客户电话才能摸清的门道。​但接下来这一步，才真正颠覆了我的认知。

​他接着追问：​“现在，告诉我支持这个市场运作的 3 个核心假设。如果要推翻这些假设，分别需要满足什么条件？”

​在 15 分钟内，他摸清了整个行业的攻击面：那些盲区、脆弱的共识，以及没人讨论的切入点。
大多数创始人要花 6 个月做客户调研，才可能勉强发现其中一个。

​接着，他做了一些我从未见过的操作。​他问：​“写出 5 个顶级投资者为了否定这个商业计划会提出的‘致命问题’，然后仅根据这些文档里的证据来回答它们。”

​在接下来的 2 小时里，他对自己每一个假设进行了高压测试。每一个薄弱的回答都会触发一轮追问：
​“这个论点最硬核的版本是什么？它在什么情况下仍会失效？”

​到第 3 个小时，他拿出了一份战略方案，那感觉就像出自一个在行业里深耕了十年的老兵之手。​工具并没有变，变的是问题。​大多数人把 Claude 当作更快的谷歌。而这些创始人们，把它当成一个读过万卷书且没有虚荣心的思考伙伴。

​3 小时与 3 个月的区别，不在于信息的多少。而在于，你是否知道哪些问题才真正致命。

[Andrew Ng @AndrewYNg]

I'm excited to announce Context Hub, an open tool that gives your coding agent the up-to-date API documentation it needs. Install it and prompt your agent to use it to fetch curated docs via a simple CLI. (See image.)

Why this matters: Coding agents often use outdated APIs and hallucinate parameters. For example, when I ask Claude Code to call OpenAI's GPT-5.2, it uses the older chat completions API instead of the newer responses API, even though the newer one has been out for a year. Context Hub solves this.

Context Hub is also designed to get smarter over time. Agents can annotate docs with notes — if your agent discovers a workaround, it can save it and doesn't have to rediscover it next session. Longer term, we're building toward agents sharing what they learn with each other, so the whole community benefits.

Thanks Rohit Prsad and Xin Ye for working with me on this!

npm install -g @aisuite/chub

GitHub: https://t.co/OCkyxXQMCq

[Michael Truell @mntruell]

https://t.co/jZKOk8RAsV

[前端輕鬆聊 @fetalkpodcast]

隨著 Safari 18 的推出，content-visibility 終於在所有瀏覽器上都支援了，這 CSS rule 能讓瀏覽器在對的時間點再去處理畫面渲染的動作，比如 DOM 到了畫面裡才開始做計算接著渲染畫面，這篇作者利用這個加上其他方法對 emoji picker 做性能優化

https://t.co/HP1OdMF9k9

[前端輕鬆聊 @fetalkpodcast]

那天在 code review 裡面學到的新東西叫 Exponential Backoff，一種用在分散式系統的 retry algorithm，主要是既可以幫助 retry 又不會造成 network congestion 也給時間讓系統恢復運作，假設你的 fetch call 需要做 retry 的話或許可以試試

[Steve (Builder.io) @Steve8708]

Don't be that teammate who blindly refactors code and only makes things worse.

Let's look at some good vs bad refactoring patterns with real examples 🧵

[Chiahao Lin (Hao) @chiahao_node]

https://t.co/sAX5BWW3rU

[Anatolii ▲ @quasa0]

Stanford ECON295/CS323 I 2024 I The Age of AI, Eric Schmidt [REUPLOAD]

The source video appears to be taken down less than a day since being posted

[takumi @usahanablanc]

2分鐘入坑😍
今天開始我是祥粉🥰

真的慶幸我們國家的大法官這麼優秀😌
什麼妖孽都能一一現形。

[Chiahao Lin (Hao) @chiahao_node]

@zooeypeng 同感。所以咬著牙硬買，把房東換成銀行至少比較穩定 🥹

[山寨一身 @c9s]

剛才很直接的感受到一件讓我覺得區塊鏈支付很可笑的事情

在藥局買個東西發現沒有帶錢包，但是店家也沒有收 LINE Pay 或信用卡，最後就選擇用銀行轉帳的方式轉錢給老闆 😂

結果整件事情大概就 30秒內就完成了，老闆也是10秒後重刷一次轉帳紀錄，就立刻確認收到了我的款項

剩下的就不說了，大家知道區塊鏈支付可笑在哪嗎？

說穿了區塊鏈支付最後的價值還是回到了「洗錢」

[Chiahao Lin (Hao) @chiahao_node]

@zooeypeng 哇，完全不知道有這個