wiizard

❤️ nvim ｜ no mispelled just kidding

[Seabird @Bouza11Juan]

美国十大银行里，已有五家进入技术性熊市：

- 美国银��：-23.5%
- 富国银行：-20.1%
- 高盛：-24%
- 摩根士丹利：-24%
- 第一资本：-25%

KBW 纳斯达克银行指数也从高点回落 15.6%，创五个月新低。

历史上银行股常领先于经济衰退见顶

[wiizard @WiizardChen]

@Rin_Mashiro_ @thsottiaux

[wiizard @WiizardChen]

@bboczeng 冷知识，勃勃本科是读光学的

[wiizard @WiizardChen]

@kimo77695 全世界都一样

[wiizard @WiizardChen]

@yetone 说明你做对了，magpie 很好用很省心

[shadcn @shadcn]

Alright, I've made the shadcn/ui skills really good at 𝙳𝙴𝚂𝙸𝙶𝙽.𝚖𝚍.

Ask for a design system and it picks a preset, then builds everything: colors, tokens, type scale, elevation, styles the primitives and blocks.

Start with a solid foundation and build something unique.

[wiizard @WiizardChen]

@theo good job

[Shawn Yin @shawnyinmr]

无聊时发现的一张图🙀

K线是纳斯达克，蓝线是道琼斯。

上次他们分化这么大时是今年六七月。

随后开始收敛，并以纳指暴跌的形式。

最近两天风格感觉有点小转换，分红高，现金流好的防御性股有些修复，因此观察了下这个spread

[wiizard @WiizardChen]

@ItsmeAjayKV agree

[Avi Chawla @_avichawla]

Another insane Jev use case!

Traditional database filters need precise, predefined conditions. But many questions are semantic:

- Is this article mainly about software engineering?
- Which topic best describes it?
- How technically deep does it appear?

These usually require moving rows into application code, invoking a model, parsing its output, and writing the result back.

pg-jev is an open-source Postgres extension that exposes Jev through SQL functions.

- jev() works inside WHERE
- jev_prob() returns a probability
- jev_choice() selects a label
- jev_score() ranks rows across ordered levels.

It needs no vector column or embedding index.

Under the hood, pg-jev batches rows, sends them to Jev, and returns typed answers that SQL can filter, sort, group, and combine with exact predicates.

The recording below runs it against real Hacker News stories stored in Postgres.

It first shows the rows, then asks Jev to find software-engineering stories, classify them by topic, and rank them by technical depth. The final query reports requests, tokens, cost, and cache hits from the database session.

GitHub repo: https://t.co/6OD0nRMgfH

(don't forget to star it ⭐)

Postgres keeps the data and controls the query, while Jev handles the part SQL cannot express as a deterministic condition.

If you want to understand what Jev is doing under the hood, I also wrote a hands-on guide to building a Jev-style model with open models, entirely locally.

Read it below.

[Gabu • rebun.dev @gabugando]

Amo NextJS, mas recentemente tem sido só derrota. Fazem alguns meses que saí da Vercel e estava tudo indo bem até precisar rodar um projeto em uma VPS de 2Gb de ram, a cada build, um crash na VPS. Resolvi brincar com algumas alternativas: Waku, Remix, Solid, mas quem me ganhou mesmo foi o TanStack Starter:
Build time caiu de 8min para 2 min, enquanto o page loading médio reduziu de 4s para 700ms.
Consumo médio de ram também baixou de 700Mb para 300Mb

[wiizard @WiizardChen]

@fiapp_pro 这是什么 agent 做的，codex吗？

[wiizard @WiizardChen]

@TokenGremlin agree

[Paweł Huryn @PawelHuryn]

Situation today:
GPT-6 Sol is like GPT-5.6 Terra
GPT-6 Luna is like GPT-5.6 Asteroid

[Chris Tate @ctatedev]

New experiment: json-render + jev

The future Generative UI is instant

Your components, your actions, your design system

Rendered in milliseconds

[Kova @kovainvest]

Read this and you will thank me later

[LIN WEI @skywind3000]

嫌 Navicat 封闭又觉得 java 写的 DBeaver 界面凌乱，臃肿又卡顿的话，可以试试 HeidiSQL：原生技术，操作飞快，开源，支持 mysql / pg / sqlite / 加密 sqlite / sqlserver / interbase / firebird 数据库，看到后面两个数据库眼熟的人，对的 HeidiSQL 就是当年 BDE 里 SQL Explorer 工具的精神续作

[OpenCode @opencode]

let's keep it going for another week

[wiizard @WiizardChen]

@bubbleboi agree

[OpenDesign @OpenDesignHQ]

Are open models overtaking closed ones?

DeepSeek V4.1 Flash outscored 11 models while costing less on everyday design tasks.
Only GPT-6 Astra scored higher. But V4.1 Flash reached 98% of its score at just 1.4% of its cost.