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Jev AI examples, page 8
407 real Jev AI builds and public demos, updated daily. Original text, metrics, and a link back to each source.
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Public Jev AI examples and demos, not official TypeSafe docs. Clients and SDKs are in the Jev GitHub projects. Paths for jev-latest, Vercel, and OpenRouter are in the September 2026 channel map.
Agent-skill repositories are listed on Jev skills on GitHub.
OpenRouter model ids recorded for Jev AI are on Jev AI on OpenRouter. Rubric and eval posts are on Jev as a judge. How the company and the model fit together is on TypeSafe AI. The pricing calculator uses the published input rate.
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@vercel_dev says Jev by TypeSafe is free on Vercel AI Gateway until Sept 25, and links the Gateway model page.
Jev by @typesafeai is free on Vercel AI Gateway until Sept 25. Build with the fastest adopted model on the Gateway at no cost. https://vercel.com/ai-gateway/mod…
Quoted @vercel
@DataChaz calls Jev a possible “Internet moment” and repeats TypeSafe’s reported figures of up to 193x faster and 444x cheaper versus Claude Fable 5.1 and GPT-6 Astra in tests. They point to a 10-page article by @0xCodila on what Jev is, how to use it, and where the claimed 100x advantage comes from.
Jev might genuinely be an “Internet moment” for AI. TypeSafe reports up to 193x faster and 444x cheaper performance in tests with Claude Fable 5.1 and GPT-6 Ast…
@GitMaxd describes an OSS demo, Agent Seek, where You.com finds pages and TypeSafe Jev re-ranks the results. They report that across 50 questions, 74% preferred the short list over You.com’s order and 86% had the answer in the top 3.
Cool little weekend OSS demo: Agent Seek You .com finds pages. @typesafeai Jev re-ranks the SERP 50 questions: 74% preferred the short list vs You .com order 86…
@airesearch12 says JevBench results are in, and that Jev is still in the lead but the race is close. The post does not list the other scores.
JevBench results are in. Jev still in the lead, but it's close.
@frevana_ai says Jev made competitor ad research 30x faster and about 90% cheaper. They typed “game,” and 20 seconds later 294 top TikTok ads across 68 brands were analyzed for about $0.02. Jev pulled the top ads from the past 180 days, scored them on stop-scroll, hook, format, and trust, clustered creative patterns, classified winners, watches, and dogs, built a leaderboard, and recommended what to make next. For gaming they report winning hooks of offer/promo and challenge accepted, and a winning format of gameplay plus UGC. They say this is what they are building at @frevana_ai, with a free link in the first comment.
Jev made competitor ad research 30x faster and ~90% cheaper. Typed “game” as the category. 20 seconds later: 294 top TikTok ads across 68 brands analyzed. Jev:…
@Layton_Gott reports that Cua built a 2.8MB, 706K-parameter model scoring 99.7% on their form-filling eval, while hosted Jev scored 83.6%. They say the small model is free, runs locally in under 1GB of RAM, and decides in one pass.
Yesterday I said Jev would open a ton of doors... 24 hours later, this exists. Cua built a 2.8MB model that scored 99.7% on their form-filling eval. Hosted Jev…
Quoted @trycua
@venturetwins says Jev can act as natural-language search on a site, for example scanning thousands of Zillow listings and classifying architecture, renovation status, or freeway proximity. They say one run finished in under 20 seconds and cost $0.18.
Jev can serve as better natural language search on websites. It can scan thousands of Zillow listings and classify properties by things you can't normally filte…
@0xRicker argues Jev could be the missing control layer for agents, routing actions in milliseconds instead of spending 5–20 seconds and an expensive LLM call on every next step. They link an article on how.
Jev could become the control layer AI agents have been missing. Instead of spending 5–20 seconds and expensive LLM calls deciding every next step, it can route…
@vercel says Jev was adopted faster than any other model in AI Gateway history. On the first day TypeSafe reached about 13% of teams, 2x the GPT-5.6 family and 6x Fable 5.1.
Jev was adopted faster than any other model in AI Gateway history. In the first day, @typesafeai reached ~13% of teams, 2x the GPT-5.6 family and 6x Fable 5.1.
@th3nolo is building an agent-agnostic permission gate with Jev and hooks, aiming to work across harnesses that share Claude Code-style hook formats.
Been building an agent-agnostic permission gate: Jev (TypeSafe) + hooks. Many harnesses copy Claude Code's hook format. Some barely have hooks at all. This make…
@irabukht says Jev cut the price of their SEO/GEO audit-and-fix agents by 90%, from about $250, by speeding reads of Search Console, analytics, citation checks, gap analysis, and page fixes. They say it is available in the Ryze AI app and an MCP/Claude connector.
Jev dropped the price of SEO/GEO fixes by 90% Agents that audit and fix a client's SEO/GEO used to cost us ~$250 Here's where the savings come from: 1/ 30x fast…
@OpenMed_AI ran four typed questions on four authored fictional notes: Jev 16/16 vs Laya 13/16, calling it a useful diagnostic not a clinical claim.
Four typed questions across four authored fictional notes, labels written before the calls. Jev 16/16, Laya 13/16. On the medication-conflict question alone: 4/…
@phil_dressler demos AI agents in a GTA-style fighter-jet contest: Astra built the sim; Jev drives their decisions.
I put AI agents in a GTA-style fighter jet competition… Astra built it. Jev powers their brains.
@kevindubois tried Jev and open derivatives like Laya inside LangChain4j agentic workflows and reported the wiring felt intuitive.
With all this hype around #Jev and open source derivatives like #Laya I wanted to see how these kinds of decision models would work in Agentic Workflows with #L…
@robj3d3 describes a doomscrolling filter: you pick a niche, Jev reads 3 days of posts and asks 8 questions each, in about 2 seconds for $0.007. It removes bait and hidden ads and judges text plus like, reply, and repost ratios. They say it is free with no signup.
Jev just solved doomscrolling. You pick a niche, Jev reads 3 days of posts and asks 8 questions each. It runs in ~2s for $0.007 😅 > removes bait and hidden ads…
@higgsfield_ai says Jev is good at content filtering and asset selection, and that DeepSeek plus Higgsfield turn the selected assets into ad creatives.
Jev is really good at content filtering and asset selection. DeepSeek + Higgsfield turn the selected assets into ad creatives.
@regalstreak says they gave Jev 5,000 real user journeys and only each user’s first 3 journeys, hiding whether the user returned. In about 10 seconds and for $0.06, Jev predicted who would quit, how confident it was, and where each journey started going wrong.
JEV IS INSANE. We gave it 5000 real user journeys from a consumer app. It only saw each user’s first 3 journeys. We hid whether they ever came back. In around 1…
@lateinteraction wishes Jev could think longer before harder decisions, and maybe return composite types such as dicts and lists, not only bools.
hear me out: jev, but with the ability to think longer before harder decisions oh and maybe with composite types like dicts and lists and not only bools 🤯
@hrishioa says Jev models fit data-pipeline work, and that using TypeSafe models for entity resolution cut costs by 99%, stayed within a percentage point of Fable, and raised throughput more than 7x. Prompts and results are linked at southbridge.ai.
Jev models are incredible for data pipeline work. Correctly integrating @typesafeai models for entity resolution cut costs by 99% while coming within a percenta…
@MKhordoo says classifiers already existed, including BERT, DeBERTa, GLiNER, and fine-tuned heads, and argues Jev is the missing piece: labels defined in code, a typed answer plus confidence, and no extra LLM call.
Yes, classifiers existed. BERT, DeBERTa, GLiNER, fine-tuned heads... Jev is that missing piece. Labels defined in code, typed answer plus confidence, no extra L…
@tamarajtran argues compaction should not be a summarization prompt. They use TypeSafe Jev to score every tool call and drop what is irrelevant, which they call instant compaction.
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 e…
Quoted @thread
@mxfp4 introduces lurk.so, a free product that finds and monitors Reddit threads so they can be cited by AI. They say 4,000 threads were scanned and alerts go to email, Discord, and Slack, made free because of Jev and @getanyapi.
everyone's making demos with Jev but nobody is making real products introducing https://lurk.so find and monitor reddit threads to get cited by AI > FREE > 4000…
@zodchiii quotes the Jev founder, formerly of OpenAI, calling Jev the biggest breakthrough they have worked on and saying it is beating everything. The post says he explains in 5 minutes why older LLMs were good at talking and bad at deciding.
Jev Founder (ex-OpenAI): "I believe JEV is the biggest breakthrough we've ever worked on This sounds too good to be true but it's beating everything" In 5 minut…
@romanbuildsaas says Jev scored 700 high-intent leads and personalized outreach messages in 40 seconds for $0.09, predicting performance, confidence, and mismatches. They say it is coming to GojiberryAI and MCP.
JEV is INSANE. We gave it 700 high-intent leads and personalised outreach messages. In 40 seconds, it predicted how each message would perform, assigned a confi…
Quoted @thread