What people are shipping with Jev.

@typesafeai Jev is FREAKING SICK!! Playing around with it to create an experimental RLS Linter for @supabase. You can check it out here: https://t.co/DI796mSm3V or view the demo

got early access to @TypeSafeAI (Jev). in my last post on autoresearch vs dream-rsi, the quiet bottleneck was: how do you score 28+ dreamt tree branches offline without waiting mi

Built a support-ticket triage simulation with @typesafeai #Jev ⚡ 5 typed judgments in parallel: • Department • Frustration • Urgency • Human request • Refund intent ~126ms avg |

Measured on 19 documents / 155 pages, mistral-ocr-latest through a @LiteLLM gateway: OCR-only vs Jev-router 155 pages billed down to → 87 19 API requests down to → 13 35.6s → 20.7s

Curated high-signal Jev (TypeSafe System One) projects — with notes, not a scrape.

@cjzafir Been working on incorporating jev into the agentic coding workflow.

Tried JEV from @typesafeai and vibe-coded a little voice-controlled browser agent.

I know I'm late to the party. But here is my mandatory Jev project. It turns your preferences in AGENTS.md file into something Jev-shaped, so your ai agent can use it sort of lik

TypeScript | 15 stars | Codebase search powered by Jev from @typesafe-ai

Go | 61 stars | mcp connector to give your AI agent direct access to typesafe ai's jev model

So here’s what I built.

Built pi-jev-context: a Pi extension powered by TypeSafe Jev that hides low-value history from model context without deleting your session. Opt-in, reversible, and configurable. K

@CombosFun_AI @typesafeai That split is what I was trying to make tangible with this little demo.

With the right ergonomics, Jev can feel like a native function call in TypeScript/JavaScript.

jev でメモリコンパクションを実装する例。ログが今の作業と関係ある/ないを分類してフィルタするっぽい。 https://t.co/fe7idXMu95

Doc-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 o

Let Me Jev That For You — ask Jev a yes or no question.

C | 52 stars | Pre-alpha PostgreSQL extension for TypeSafe AI (Jev) categorical classification

@every @jackcheng @typesafeai a prose linter. it asks Jev ten yes-or-no questions per paragraph (is the claim hedged three times, does the closer just restate the paragraph, is the

check if code is malicious before you run it, built with jev from @typesafeai https://t.co/YJRT5KCAzA https://t.co/8wqzgnpPaF