when a designer gets access to Jev
jev-superpowers
An agentic software-development skill set built on obra/superpowers, where Jev in the cloud or open-weight Laya locally gates architecture choices, package vetting, shell commands, and completion checks.
- Category
- Tools & Integrations
- Published by
- Community
- Author
- AkashPriyadarshii
- Added
- 2026-09-22
Tagscommunityskillscoding-agentagentsopen-models
Highlights
- Upgrades five superpowers phases: jev-brainstorming, jev-writing-plans, jev-executing-plans, jev-systematic-debugging, and jev-verification.
- Backend-agnostic: TypeSafe cloud (jev-1.13.0) with TYPESAFE_API_KEY, or a fully offline Laya 421M ModernBERT server via TYPESAFE_BASE_URL.
- Reported design targets: near-zero package hallucination, 33-38 ms local gate latency, about $0.00001 per cloud decision, 24/24 offline tests.
- Ships a toolchain suite: git-jev for pre-commit gates, jev-scout for package vetting, jev-axi, jev-guard, supercov, and jev-seo.
- The README labels its benchmark table design targets measured on the maintainer's setup and asks users to reproduce them first.
Quickstart
bash
export TYPESAFE_API_KEY=YOUR_API_KEY
bash install.shWatch out
MIT-licensed. A community project, not affiliated with TypeSafe; needs a TypeSafe API key for the cloud backend or a local Laya server, and its benchmark numbers are maintainer-measured design targets.
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From the community
Posts from builders shipping with Jev right now.
When a designer gets Jev
Full Jev video tutorial
Full Jev Tutorial What it is, how you can build with it and what new applications it can unlock → 0:00 Intro → 0:34 Jev explained → 4:06 API setup → 5:59 Demo 1: Voice-controlled browser → 11:33 Demo 2: AI memory → 17:27 Demo 3: YouTube predictor
The case against Jev-scored compaction
This is a terrible compaction strategy that fundamentally doesn't understand how compaction and context management work. Seems like a lot of people are confused so let's break this down. 1. Compaction isn't a filter The role of compaction is to clean up history to keep the 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
Classifying rows in DuckDB
I made a DuckDB extension where you can use @typesafeai 's Jev to do quick classification of rows in any csv/parquet file or duckdb table about 10sec for 1k rows ~ better than using an LLM, way more ergonomic than a classifier game-changing for data analysis!
A playable 16-judgment demo
typesafe's jev is fun! live demo you can play with: typesafe-demo.val.run
AI multiple choice, not essay writing
WTF is Jev by @typesafeai? Here’s the tl;dr ELI5: Think AI multiple choice, not AI essay writing. It doesn’t chat. It makes decisions your software can act on: “Spam or not?” “Which tool should this agent use?” “Does this need a human?” The exciting part: roughly 200x faster Show more