Projects built with Jev

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OpenRouter: let Jev choose the modelIntroducing typesafe/jev-router: a cache-aware model router powered by Jev and @typesafeai The Jev Router picks the best model and reasoning effort for each request, balancing quality, speed, and cost. Here's how it works 👇🏻OpenRouter1.1M views on X

jevgrep: focused research for coding agentsIntroducing jevgrep - a research agent CLI powered by jev from @typesafeai that reduces your coding agent cost by 40% (verified on SWE-bench) Make sure to use the built in skill so your coding agent knows to use jg for context collectionDavid20.8K views on X

jevopt: smarter compiler inliningCan Jev optimise the size of compiled binaries better than clang -Oz? Turns out it can (sometimes)! Introducing jevopt: making intelligent compiler optimisation decisions with Jev. I used Jev to make intelligent inlining decisions at each LLVM IR call-site. Here’s how I did it.Ramneet Singh1.1K views on X

Superterminal: search your terminal naturallywhen I connect terminal with JevSonny6K views on X

ASIMOV: filter CLI output in plain EnglishThe latest @ASIMOV_Platform release lands a built-in `--jev=NOUL` output filter, enabling agentic harnesses such as Hermes to offload simple natural language postprocessing decisions to Jev, a System One model Look ma, here just casually turning my LinkedIn network into JSON-LDArto Bendiken5.9K views on X

Instant context compactionfound 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 irrelevanttamara≈ 3.6M views on X

Decisions from the command lineEvery agent harness can now use Jev npm install -g ai-cli → ask yes/no questions → choose between options → score against your criteriaChris Tate116.1K views on X

Instant variable generationanother demo for jev for ~instant variable generationkhaled1.1K views on X

Instant generative UINew experiment: json-render + jev The future Generative UI is instant Your components, your actions, your design system Rendered in millisecondsChris Tate1.3M views on X

A prompt difficulty classifierprompt classifier before user hits send jev is very fast and cheap so we can check the difficulty of the prompt every time user finish typing if its a simple prompt, we show fast mode and let the user decide if they want it or noKevin Grajeda5.3K views on X

A draft quality gateit's f*cking insane Jev sat between GPT and me, killing every draft that broke my rules before i saw it. good setup. then Jev did not answer. the agent decided silence was safer and stopped sending me anything at all. took a second agent to unstick it. your checker needs aMnimiy17.9K views on X

Session replay to bug fixesJEV is INSANE. We gave it 3 million replay events In 40 seconds, it watched 3,247 sessions, caught 132 rage clicks, 116 dead clicks and 95 JavaScript errors, and opened 213 draft PRs to fix them. All for just $2.17. JEV can also flag abandoned forms, rank every issue byTaras98.5K views on X

A Jev query plannerI used Jev to build a query planner! With some tuning, I sped up Postgres queries on the join order benchmark by 12%. Here's what I didMichael Malis14.3K views on X

Jev compaction for OMPIf you use omp, you're missing out on jev based compaction It helps your agent optimize token usage with 30 to 55% less context. $0.0005 a pass What it does: - Scores every old tool output with Jev - Keeps what's needed - Parks the rest on disk - Remembers its decisions soJerry the Martian1.2K views on X

A plain-English logic interpreterJev can't reason. So I built an interpreter that reasons for it. It runs a logic language where the facts and rules are plain English.Shawn Simister38.9K views on X

Supabase RLS linter@typesafeai Jev is FREAKING SICK!! Playing around with it to create an experimental RLS Linter for @supabase. You can check it out here: or view the demo 📺Ali Waseem20.7K views on X

A page-by-page OCR routerDoc-OCR router using Jev @typesafeai A Jev-powered router that looks at a PDF page by page, decides which pages actually need OCR, extracts the rest locally. Result: save cost on # OCR pages + speedMisbah Syed26.1K views on X

JevalsI wanted an easier way to test my jev requests and see if my results are improving, so I built jevals! It's a local workbench for testng the Noul, Choice, and Score primitives. You can mix requests as well. You can run a seed command to see and play with some of the examples inNick DeJesus 🛒🎉 - Former Unpaid CTO @BTPipeline1.7K views on X

Tester Army E2Ee2e + jev from @typesafeai ⚡ I'm building an open-source framework for running e2e tests with agents. supports web, mobile (and more!) available soon:Oskar66.4K views on X

Corent model routingCorent’s brain uses @typesafeai Jev now. Not to generate the output, to make the decision before the output gets generated. When a request comes into Corent, you don’t need to tell us which model to use. You send the prompt, the workload and the quality level. Then Jev helpscorent109.1K views on X

An AI-writing slop detectorYou can use Jev to flag all the slop that Opus likes to writeChase Lean3.5K views on X

Abide coding-agent rulesbest coding agent use case for Jev: enforcing rules a linter can't coding agents tend to break rules and some rules can't be codified Jev can now score every turn against such rules and tell the agent what to fix asap open-source:Ohans Emmanuel110.1K views on X

Android end-to-end testingWas curious how jev performs for e2e testing on a real android device. Both started with the same prompt and 15 test steps. Well, jev was ~14.8x faster than deepseek + vision navigating through wikipedia.Kevin Kern1.7K views on X

Measuring progress in agent tracesGot early access to @typesafeai Jev and spent a few hours building on it. The problem I keep hitting: agent traces tell you which tool ran, how long it took, what it returned but never whether the agent is actually getting anywhere. An agent editing, testing and reverting theKaushik1.6K views on X

Claude Code context compactionI got access to Jev and immediately plugged it into Claude Code to see if it actually FIXES the biggest pain of agent workflows: context compaction > result: pretty wild Quick context for those who missed it: Every Claude Code session has a context window that fills up fastkaize3.4K views on X

Cascade Search typed query filtersA search bar that knows when it doesn't know. cascade-search is a 27K-parameter model that parses queries like "open bugs from sam since last week" into typed filters, in your browser, in 0.25 ms. When it isn't sure about a word, it asks Jev. Only that word.Zaid5.4K views on X

Parallel adversarial browser testingthanks to @typesafeai's Jev we now have massively parallel browser-based adversarial testing suite that tries to break each release. and it costs pennies.Rafal Wilinski≈ 386.9K views on X

Predicting the next shell commandJev picking the next command from shell historyThorsten Ball≈ 118.3K views on X

Jevcal confidence-threshold calibrationEveryone picks Jev confidence thresholds by vibes. 0.95? 0.5? I built jevcal. Give it your data and say "I need 99% accuracy". You get the exact threshold, how much Jev can handle, and how much still needs an LLM. Open source, one command. @typesafeaiAbhishek kothari3.7K views on X

Skill Router for Claude CodeJust hacked a fun little project - Skill Router (Open source) using Claude and Jev @typesafeai Why? I have ~ 90 Claude Code skills installed and use maybe five. The rest are fine, I just forgot they existed, and Claude won't reach for a skill on its own unless you call it. SoLomesh Dutta2.5K views on X

Nanocode with selective memory compactioni added Jev compaction to a small agent with searchable memory. this is a fork of nanocode with some extra tools to grep a memory.md file + use Jev compaction to remove unnecessary memories.Kyle Jeong2.9K views on X

Touchpress mobile end-to-end testingmy mobile e2e testing library powered by @agent_device and AI sdk now supports Jev from @typesafeai Same test, same loop: Jev: 29s, $0.003 Haiku 4.5: 37s, $0.07Robert Soriano≈ 14.5K views on X

Fourteen checks for every pull requestgot Jev to review my PRs. ~200x cheaper than Claude and it answers in half a second 6 real PRs in the video. $0.00007 each. 1,000 PRs = 7 cents vs ~$14.50 on Opus 5 paste a diff → ONE call to @typesafeai → 14 typed checks come back as probabilities: hardcoded secret, sqlPaolo Rosson≈ 352.8K views on X

Natural-language queries inside PostgreSQLI think I just cooked something 🔥 jev(): a PostgreSQL extension that searches your whole database in natural language. No index, no embeddings, just one function. WHERE jev(people, 'could work from home') or WHERE jev(people, 'name sounds european') 129 rows judged in ~1sZachi≈ 432.8K views on X

A codebase complexity classifieri built a codebase classifier with Jev and this might be the solution to overengineered code that agents create what should I test Jev on next?vogel≈ 97.5K views on X

Email fraud detection with Jev and KimiJev + Kimi K3 for fraud detection! TLDR: Jev classified 100 emails in 1.42 seconds, then I routed the uncertain cases to Kimi K3. The full pipeline got 96/100 correct for only ~$0.07. Video is not sped up, check out the live run! Here was my process: I gave Jev 100 emails toHassan≈ 58.2K views on X