Dan

🇹🇼 iOS Developer, Monster Hunter, Pokémon Master,  fan

[Daiki Matsudate @d_date]

https://t.co/QFbufEdUia

[Dan @dan_phy1988]

@mangoice 🙌

[Andrej Karpathy @karpathy]

A few random notes from claude coding quite a bit last few weeks.

Coding workflow. Given the latest lift in LLM coding capability, like many others I rapidly went from about 80% manual+autocomplete coding and 20% agents in November to 80% agent coding and 20% edits+touchups in December. i.e. I really am mostly programming in English now, a bit sheepishly telling the LLM what code to write... in words. It hurts the ego a bit but the power to operate over software in large "code actions" is just too net useful, especially once you adapt to it, configure it, learn to use it, and wrap your head around what it can and cannot do. This is easily the biggest change to my basic coding workflow in ~2 decades of programming and it happened over the course of a few weeks. I'd expect something similar to be happening to well into double digit percent of engineers out there, while the awareness of it in the general population feels well into low single digit percent.

IDEs/agent swarms/fallability. Both the "no need for IDE anymore" hype and the "agent swarm" hype is imo too much for right now. The models definitely still make mistakes and if you have any code you actually care about I would watch them like a hawk, in a nice large IDE on the side. The mistakes have changed a lot - they are not simple syntax errors anymore, they are subtle conceptual errors that a slightly sloppy, hasty junior dev might do. The most common category is that the models make wrong assumptions on your behalf and just run along with them without checking. They also don't manage their confusion, they don't seek clarifications, they don't surface inconsistencies, they don't present tradeoffs, they don't push back when they should, and they are still a little too sycophantic. Things get better in plan mode, but there is some need for a lightweight inline plan mode. They also really like to overcomplicate code and APIs, they bloat abstractions, they don't clean up dead code after themselves, etc. They will implement an inefficient, bloated, brittle construction over 1000 lines of code and it's up to you to be like "umm couldn't you just do this instead?" and they will be like "of course!" and immediately cut it down to 100 lines. They still sometimes change/remove comments and code they don't like or don't sufficiently understand as side effects, even if it is orthogonal to the task at hand. All of this happens despite a few simple attempts to fix it via instructions in CLAUDE . md. Despite all these issues, it is still a net huge improvement and it's very difficult to imagine going back to manual coding. TLDR everyone has their developing flow, my current is a small few CC sessions on the left in ghostty windows/tabs and an IDE on the right for viewing the code + manual edits.

Tenacity. It's so interesting to watch an agent relentlessly work at something. They never get tired, they never get demoralized, they just keep going and trying things where a person would have given up long ago to fight another day. It's a "feel the AGI" moment to watch it struggle with something for a long time just to come out victorious 30 minutes later. You realize that stamina is a core bottleneck to work and that with LLMs in hand it has been dramatically increased.

Speedups. It's not clear how to measure the "speedup" of LLM assistance. Certainly I feel net way faster at what I was going to do, but the main effect is that I do a lot more than I was going to do because 1) I can code up all kinds of things that just wouldn't have been worth coding before and 2) I can approach code that I couldn't work on before because of knowledge/skill issue. So certainly it's speedup, but it's possibly a lot more an expansion.

Leverage. LLMs are exceptionally good at looping until they meet specific goals and this is where most of the "feel the AGI" magic is to be found. Don't tell it what to do, give it success criteria and watch it go. Get it to write tests first and then pass them. Put it in the loop with a browser MCP. Write the naive algorithm that is very likely correct first, then ask it to optimize it while preserving correctness. Change your approach from imperative to declarative to get the agents looping longer and gain leverage.

Fun. I didn't anticipate that with agents programming feels *more* fun because a lot of the fill in the blanks drudgery is removed and what remains is the creative part. I also feel less blocked/stuck (which is not fun) and I experience a lot more courage because there's almost always a way to work hand in hand with it to make some positive progress. I have seen the opposite sentiment from other people too; LLM coding will split up engineers based on those who primarily liked coding and those who primarily liked building.

Atrophy. I've already noticed that I am slowly starting to atrophy my ability to write code manually. Generation (writing code) and discrimination (reading code) are different capabilities in the brain. Largely due to all the little mostly syntactic details involved in programming, you can review code just fine even if you struggle to write it.

Slopacolypse. I am bracing for 2026 as the year of the slopacolypse across all of github, substack, arxiv, X/instagram, and generally all digital media. We're also going to see a lot more AI hype productivity theater (is that even possible?), on the side of actual, real improvements.

Questions. A few of the questions on my mind:
- What happens to the "10X engineer" - the ratio of productivity between the mean and the max engineer? It's quite possible that this grows *a lot*.
- Armed with LLMs, do generalists increasingly outperform specialists? LLMs are a lot better at fill in the blanks (the micro) than grand strategy (the macro).
- What does LLM coding feel like in the future? Is it like playing StarCraft? Playing Factorio? Playing music?
- How much of society is bottlenecked by digital knowledge work?

TLDR Where does this leave us? LLM agent capabilities (Claude & Codex especially) have crossed some kind of threshold of coherence around December 2025 and caused a phase shift in software engineering and closely related. The intelligence part suddenly feels quite a bit ahead of all the rest of it - integrations (tools, knowledge), the necessity for new organizational workflows, processes, diffusion more generally. 2026 is going to be a high energy year as the industry metabolizes the new capability.

[Ethiel A. @enthusiastDev]

Whenever we integrate a Stream into a Flutter BLoC, many codebases handle it manually with subscriptions, listeners, cancellations, and cleanup in close().
It works… but it creates a lot of boilerplate and a surprising amount of risk: forgotten cancellations, leaks, and unexpected behavior when multiple subscriptions come and go.

emit.forEach is a cleaner and safer option.

Instead of managing the subscription lifecycle yourself, emit.forEach connects your stream directly to your BLoC state in a declarative way. It listens, maps values to state, handles errors, and cleans up automatically when the BLoC is disposed.

Less plumbing. More clarity. Fewer bugs.

I added a small before/after snippet in the visual to show how much simpler it becomes with emit.forEach.
It’s one of those features that quietly makes your BLoC architecture feel more intentional and robust. 🚀
Follow me and @fluttergigs for more!

[Kilian Schulte 💙 @schultek_dev]

The amount of raw knowledge and experience in this document is just 🤯🤯🤯🤯

https://t.co/UIvHZl2ANM

[Mickrich384 @mickrich384]

Holy shite!
shorthands merged on master!!!!

https://t.co/jHdPcBVppV

[Dan @dan_phy1988]

@mufeedvh access

[Awni Hannun @awnihannun]

We heard developer feedback on Monday that the MLX Swift LLM API is hard to get started with. So we went to work. We made a new and improved streamlined API.

Now 3 lines to load an LLM or VLM and start a chat session in a Swift project.

Happy last day of #WWDC25 !

[forest @ephemeralapps]

If you want to understand the future of iOS:

App Intent Snippets

https://t.co/BUU2pY2fie

[Tahiro Agbanwa🇲🇲🇬🇭 @squirelBoy360]

@FlutterDev #flutter #iOS26 @mahersafadii @luke_pighetti

Flutter is cooked. JIT has been killed in ios 26 https://t.co/RdZvjoQ2m8

[Kate Lovett @k8lovett]

Loving the new Apple’26 design language! ✨

We're carefully planning our Cupertino design updates in #Flutter for long-term quality and maintainability, similar to Material 3 Expressive.

Read more: https://t.co/Vx6ZE2TtFZ

What did you love from #WWDC?

[Tw93 @HiTw93]

#工程师学习 一张图的方式看明白 .git 文件夹里面都有哪些内容，挺清晰。

[何雅瑄 @yaxuanhe_zh]

【Personal Rules】

這篇有趣！好好奇其他人的 Personal Rules。
讀完後想到自己的幾點：

- 只買很喜歡的東西
- 比起吃東西，更喜歡喝東西（茶和咖啡是不可割捨之物）
- 除了 Twitter 和 BeReal 外，不會在社交媒體上發文

本日推薦 "Useful Personal Rules"：https://t.co/zTh7Q5HEhY

[無情的 CRUD 機器 @CRUD_Machine]

【每天推薦一篇文章】Code Review 的壞味道

剛剛巡到一篇 Code Review 的文章，感覺挺適合轉貼上來分享給大家：

Code review 的好處與 bad smells - Huan-Lin 學習筆記
https://t.co/ZPVxiJPu7V

---
我們在 1/13 的時候分享過這兩篇：

從 Code Review 的小事看大事 - Potioneer's Essays
https://t.co/2SoPzD3Fc4

Google 教我如何進行 Code Review | Summer。桑莫。夏天
https://t.co/WAUe1TR4du

藉由這些文章，我們能大約知道 Code Review 該看哪些東西，又有什麼好處等等（問就是 FOUR EYES!）

而今天轉貼的這篇 Huan-Lin 大大的〈Code review 的好處與 bad smells〉，則提到了另一個有趣的點：

「有問題的 Code Review 會有哪些壞味道？」

文章裡面列了三項，並且每一項都用了一小段來解釋。這邊就按照慣例，簡單列一下收進我的筆記就好：

- 馬馬虎虎：我很忙，看個意思意思就好
- 合作無間：自個兒人，幫個忙唄
- 粗魯評論：挑毛病、戰習慣、叫你改就改

有採用 Code Review 的朋朋們，也可以觀察一下團隊有沒有提到的這些狀況

那麼，今天的轉貼就到這邊。我們明天見～

[图拉鼎 @tualatrix]

今天朋友告诉我一个 macOS App 的 Debug 技巧：只要在任何 App 启动时加“-_NS_4445425547 YES”这个参数，就会在菜单栏获得一个超有用的🐛菜单，方便 Debug。超赞的！

比如我将 Reeder 这款 App 进入了这个模式：

来源：https://t.co/mpwElLMV97

[Eason @eason9487]

主計處的薪情平台的原來有提供到年薪 400 為止的細部資料，但不知道為啥只畫到 200 萬，後面就不畫了。年薪在 200 ~ 400 的人想看到自己的那條紅線，在 DevTools 執行這個就有了
Object.defineProperty(DDK.exps.limitdata, 'valueMax', { get: () => 4000000 });
DDK.exps.draw(DDK.exps.getData());

[Huli | lang: zh-Hant-TW @hulitw]

寫了一篇日本軟體工程師薪水的文章
有些數字沒有很精確，抓得比較隨意
但附了一些參考資料讓想深入研究的人可以自己研究

除此之外也順便把工作依照薪水分了四個區間
這樣討論起來才能在同個點上
每次看到一堆不同區間的混在一起討論
就覺得這樣應該討論不出什麼東西吧 😅

https://t.co/ZYKqNYweRW

[Sandro Maglione @SandroMaglione]

💡 Dart tip 💡

Did you know dart supports destructuring classes? 🪄

Class name + `:` followed by property name

Patterns are powerful 🔥