Claude me integró Jev con Playwright para buscar usados. Lee unos 26 artículos por minuto y decide qué hacer con cada uno en 406 milisegundos Descartó los que no encajaban con lo que busco, ofertó por los que sí y hasta les mandó un mensaje a los vendedores cuando faltaba algún Show more
PatternsAutoformat
Structure recovery
Reconstruct Markdown from unformatted text in two requests: stitch split lines, then classify every block's type.
- Category
- Patterns
- Also known as
- Autoformat
- Related terms
- 3
- Directory entries
- 1
- Docs
- docs.typesafe.ai
- Added
- 2026-09-24
Definition
The cookbook processes a 28-line memo with 16 Noul line-pair questions that stitch split sentences, then 62 questions that classify each block's type and companions — 10,211 tokens in 0.8 seconds. Join cutoffs of 0.2 after dangling lines and 0.5 after terminal punctuation healed 11 line breaks.
It is a clean example of a justified second request: the blocks do not exist until the first pass has stitched the lines. Stitching and typing are separate judgment layers, so a bad stitch can produce a clean-looking document with the wrong structure.
Tagspatternsformattingbatching
Related terms
Definitions that connect to this one.
Second requestA follow-up call that is only justified when code cannot build the second request until it has the first answer.PatternsNoulThe yes/no primitive: one probability from 0 to 1, where the value is the answer and no separate confidence is returned.PrimitivesParallel questionsBatching many questions into one request instead of many calls, which is dramatically cheaper and faster with identical answers.Patterns
From the directory
Reconstruct Markdown from unformatted text in two requests: 16 Noul line-pair questions stitch split sentences, then 62 questions classify each block's type and companions.
Cookbooks & DemosDocs#official#cookbook#formatting
Official
From the community
Posts from builders shipping with Jev right now.
A second-hand shopping agent
Predictive spreadsheets
Another crazy @typesafeai Jev example: Predictive spreadsheets Spreadsheets recalculate numbers, not meaning. Jev reads intent. Type "Urgency" at the top of a column and, as you type, it figures out you want each row rated from "no follow-up needed" to "urgent" in ~100 ms.
@dabit3
Also have been playing with @typesafeai Jev, insane! So many immediate use cases and new apps are possible. What a time to be a builder! Sharing some experiments here starting with: Keystroke oracle / predictive launcher: Your launcher ranks by aliases, fuzzy match, and
The compaction plugin, in Chinese
连 JEV 的联合创始人 @CompleteSkeptic 都亲自下场转发点赞：这是 JEV 正确的打开方式！ 大家在 Claude Code 里写长代码，最恶心的就是上下文一满，系统就卡住 10 秒去写总结小作文 开发者 @tamarajtran 刚刚开源了这个插件：利用 JEV Show more
found the perfect use case for @typesafeai Jev: instant compaction in 2026, why is compaction still a summarization prompt? Jev can make it instant by scoring every tool call and dropping what’s irrelevant
WTF is Jev, and 9 things people are building
TL;DR of my new article: WTF is Jev by @typesafeai, and the 9 things people are already building with it. The thesis: 𝗮 𝗰𝗼-𝗰𝗿𝗲𝗮𝘁𝗼𝗿 𝗼𝗳 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝘀𝗽𝗲𝗻𝘁 𝘁𝘄𝗼 𝘆𝗲𝗮𝗿𝘀 𝗶𝗻 𝘀𝘁𝗲𝗮𝗹𝘁𝗵 𝗼𝗻 𝗮 𝗺𝗼𝗱𝗲𝗹 𝘁𝗵𝗮𝘁 𝗰𝗮𝗻𝗻𝗼𝘁 𝘄𝗿𝗶𝘁𝗲 𝗮 Show more
x.com/i/article/2100…
Voice-controlled computer use on a Mac
I built a voice controlled computer-use for my mac using @typesafeai's Jev and it's INSANE how fast it is! I can dictate "open the notes app and create..." and the app opens before I even finish my sentence.
The use cases Jev unlocks
You still don't understand the use cases Jev unlocks. I've been waiting for something like this since early ChatGPT models. prediction: we will see the fastest-growing SaaS by MRR in history within the next month or two