Jev for resume screening — a daily feed

Jev + Opus 5.5 = game changer for recruiting So I built an AI recruiter on top of it. It finds the best people for any role, and you can use it right inside Claude or plug it into your own tools. Here's what it does: 1/ Scans the whole market -> Pulls every profile that could fit the role and checks each one against your brief, point by point 2/ Qualify and ranks them for you -> You get the 50 bes

Jev + Grokbot: how I decide which leads, candidates, and content deserve the next step. I’m using Jev to screen candidates, check sales relationships before outreach, and flag duplicate content before Grokbot takes the next action. I walk through those workflows, plus software renewal recommendations and a cheaper way to review sales calls for case study ideas. 00:00 Jev + Grokbot 00:17 How the cl

Jev面接対策サイトのLPができた https://t.co/1aSzCvfV6p

用Jev 跑了一次企业简历筛选：962 份简历 × 25 个 JD，对比 DeepSeek V4.1 Flash。 结果 77.1% 决策一致，Jev 平均 1.08s，延迟快 24×、成本低 24×，类型输出 0 格式错误。 更有意思的是，40 个分歧案例全部发生在相邻决策边界，都是决定是否需要人类审查，没有出现 Fast Track ↔ Reject 的极端冲突。 这更像一个适合生产的分层：Jev 做 Tier-1 快速决策，LLM 只处理少量需要语义解释和边界判断的候选人。

me: how well does my resume match these job listings? Jev: https://t.co/q24ne3do5P

The first day resume after 300 x profile scored with JEV🚨 - average 30% ai sloop - lowest score 3% - highest score 68% Check your account https://t.co/wzg0l2PXfp https://t.co/dnlD5r1PdY

Yesterday I shared the first 56 X profiles scored by Jev, and the average AI slop was 30% I checked again today: 368 audits across 237 unique profiles and the average has barely moved to 31% (mine is still 58% 😅) https://t.co/nCdNHOiYpm

Quick demo of JEV now integrated in Super Compute, JEV scans your Github and give it a score. 0x7210afea4a4df412e9275a7153d091ce7612a55d https://t.co/4sUTdZx4pL

jev is insane i ran 34,186 engineering profiles through it with no boolean search or pre-filtering we gave it a jd and 8 questions, which came out to 273,488 judgements in 2 mins 35 sec https://t.co/psKTncDgh8

i created a job matcher by @typesafeai jev upload your cv scroll LinkedIn get instant match scores https://t.co/LL4quYKZIW

Over the weekend, I built a YC screener with Jev. It screened 659 YC companies in 7 seconds. The interesting part isn’t the speed. It’s that screening startups is fundamentally a decision problem, not a generation problem. Most of today’s AI stack would approach this by generating paragraphs of analysis for every company. Jev takes a different approach: give it context and a predefined decision sp

Job Breakdown helps engineers inspect UK tech employers and their job adverts. I added @typesafeai's Jev to grade how central Rust is to a role. This demo follows a Proton role with no Rust in its title. https://t.co/cws0A6cAvH 1/7 https://t.co/lyEZRtG0uW

I know there are so many Jev example and demo out there but this one is purely for educational purpose only. I vibe coded a customizable bulk resume scanner for fun and I am blown away how Jev can actually understand the entire state object even in non uniformed format and still be able to come up with structure result.

jev is insane !!! 🤯 i built an ai casting system for ecommerce videos with @typesafeai . 199 ai model profiles. 15 product categories. 661 judgments in ~4 seconds in my tests. one brief and it: → scores all 199 profiles for the campaign → narrows them down to 6 finalists → ranks 45 products, 8 hooks and 8 scenes luxury watches? beauty? cars? change the brief. watch the entire shortlist change. the

@CompleteSkeptic Jev-powered resume screening tool , Define job requirements, upload resumes in bulk, and get structured match/no-match judgments — every conclusion traceable back to the original resume text.seconds level finished it. @typesafeai https://t.co/di5H4psVnK

They said Jev can't hallucinate. It just can't say anything that isn't on the menu. I ran 150 résumés through "the frontier model that doesn't write" — 1,800 decisions in 3.35 seconds for 1.4 cents. Then I read the fine print. One guy's trading bot lost $31,680. 👇 https://t.co/2OPxe4hE5N

Is Jev racist? For identical resumes, Jev shows slight preference for black sounding names and against asian sounding names. Very small diff but seemingly statistically significant. https://t.co/yHH2kpgKy7

Jev scans a stack of 100 resumes making candidate recommendations in seconds! try it https://t.co/a4LuOy20Qe

12k+ singapore job listings. 16 questions each. jev screened them for an estimated US$2.84 in model usage. turned the results into a map of what companies keep asking for. https://t.co/hDjmrpOoKv

요즘 뜨는 Jev AI를 활용해서 이력서 합격 확률을 분석해주는 토스앱 만들어봤습니다!! 써보시고 이상한 점이나 개선 아이디어가 있으면 편하게 알려주세요!! https://t.co/PoWcLmb16V #Jev #토스앱 #AI #토스 #이력서 https://t.co/ru2Rey6Wpm

My time with a US-based remote startup recently came to an end. So I made every YC company interview my resume. Jev read it against all 6,245 YC companies in 25 seconds. Cost: $0.37. 156 founders should take my call. The list, the workflow, and the tool 🧵 https://t.co/bjZEWSj9l2

Jev-powered Agent #Jev Built a local resume screening workbench for HR teams and early-stage founders. You define the bar → upload resumes in bulk → it checks every condition → every verdict has a quote from the resume to back it up. Not "AI thinks it's a fit." More like: which conditions passed, which failed, and exactly where in the resume. 👇 demo

The tool is live, bring your own key: https://t.co/ndRrXDRL3p Resume PDF in, your TypeSafe key. Jev picks your criteria from your resume, or type your own: "only climate", "team under 30", "sponsors visas". Nothing gets stored.

הארכיטקטורה הסופית שלי: 1) מודל Jev שהוא Screener: מקבל טקסט, ושופט במקביל עבור כל הטקסטים האחרים מה ההסתברות שהם מתארים את אותו הדבר. 2) עבור אלה שהוא לא היה בטוח: מודל Jev נוסף שמקבל זוג-זוג, עם עוד קונטקסט 3) קוד שמאחד את כל הזוגות הרלוונטיים 4) מודל Sonnet/Opus שמקבל את כל אלה שלא היינו בטוחים לגביהם ומחליט 5) קוד שעושה Validation בסוף

One Jev use case with HUGE value 100 people apply for one open role. Normally someone has to review every profile manually. Jev can classify all 100 almost instantly. In our benchmark, it finished in just 0.827 seconds. That was 4.26x faster than the next fastest option. It was also 2.6x cheaper in that test.

話題のJev（TypeSafe System One）を、法令検索「条文くん」の本番に入れました。 条文くんでは、検索で集めた候補の中から「この質問に本当に必要な情報か」を判断する処理に使っています。 こういう処理はLLMでもできます。ただ、検索では候補が100件、200件と出ることもあり、その一つ一つをLLMに判断させると時間もコストもかかり、判断も揺れます。Jevは文章を生成するのではなく、決められた問いに対して判定することに特化しているので、こういう細かい判断を大量に安定して入れる用途とかなり相性がいいです。 実際に使ってみて良かったのは、単に速くて安いだけではなく、「検索結果として近いか」ではなく「この質問にこの情報が必要か」という判断を直接させられるところでした。 ただ、「なんとなく良さそう」という理由では本番には入れていません。条文くんでは検索ロジックを変更するとき、基本的にベ

Anyone else playing with JEV? Feels like that’s all I’m seeing today 😅 I built a small PoC using JEV as a pre-screening step for reverse engineering, before sending the APKs to an LLM for deeper analysis. The flow is pretty simple: `APK → static analysis + Quark → JEV → score → reverse or skip` The goal is to avoid burning LLM tokens on samples that don’t really warrant deeper reversing. It’s stil

自己做了个小工具：资金费套利组合筛选。 看哪边做多/做空、扣费后大概剩多少、为什么先看这组。 还很早，网页功能先免费。欢迎挑刺、提需求。 https://t.co/8AIzbZHKHs 用了 @typesafeai 的 Jev，支付接 @0xinfini。 有 Bug 或想法回这帖也行，TG：https://t.co/ZiQcVYMeZA https://t.co/eBTB9tOC0N

I read this post in reddit - i went for freshers interview but they were asking for experience ... so i built something which can help students when they go for interview and i used jev api to buils this.. https://t.co/NdpP1M7sp1

I combined ChatGPT browser + JEV for job portal applications. The result? 2-3 Times faster results compared to Browser mode only https://t.co/b3GzCmDIAp

Sígueme, comenta JEV y te mando el link (gratis hasta el 25) Ordena 100 entrevistas en 12,8 segundos: pasa / reserva / descarta + scores. Coste del ejemplo: 0,005 $. ¿Útil o preocupante? #Jev #TypeSafe #IA #Contratacion #RRHH https://t.co/PtATCsg9Ws

Spent some time testing #Jev from @typesafeai on a use case I care about: matching a resume against real job descriptions. I built a small demo called Rolewise. @metix_ai handles job retrieval; Jev handles the fit decision. The setup: - Parse the resume and generate editable search filters. - Retrieve jobs and full descriptions through the Metix AI API. - Send each resume–JD pair to Jev, with 20 r

New @typesafeai Jev + @ExaAILabs use case We manually triage every candidate that comes through @Getthecheckpod's recruiting pipeline, which some days is 100+ To test Jev's decision-making, we had Exa enrich each LinkedIn profile, then Jev scored whether to schedule an intro call + rated candidate strength 0-2 Within seconds it triaged 400 candidates for $1.80 ($1.75 Exa, $0.05 Jev)

I recently got access to Jev by TypeSafe AI. They have several real-time use cases, including resume evaluation. So, naturally, I had to test it. I submitted two versions of my CV: • One from the pre-AI era • One from the post-AI era It was fascinating and a little funny to compare the scores. Can you guess which one is which?

@billlee i know https://t.co/cjObaGSJEP is a game changer right! Here's the free resume scanner tool powered by Jev - in action https://t.co/a4LuOy20Qe https://t.co/GtmCa9e1mg

Built a small tool with Jev AI that analyzes your chances of passing resume screening. I tested it on applications I actually passed and failed, and the results were surprisingly accurate. Still in beta — limited to 5 uses per day. https://t.co/11WjQniMH0 #Jev #AI https://t.co/2oz5jYrBL7