when a designer gets access to Jev
Robo Harness
An SO-101 workbench where an evaluation model or rules baseline picks bounded joint steps from typed candidate actions: decision runs are spend-capped via the Vercel AI Gateway and drive a real LeRobot arm or mock hardware.
- Category
- Cookbooks & Demos
- Published by
- Community
- Author
- grmkris
- Added
- 2026-09-22
Tagscommunitytypescriptroboticsmcpagents
Highlights
- The decision runner calls Jev through the AI SDK experimental_evaluate API on Vercel AI Gateway; cumulative spend is capped by ROBO_JEV_BUDGET_USD, default 10.
- Free Gateway credits exclude Jev, and zero data retention is opt-in via ROBO_JEV_ZDR=1 on Pro or Enterprise plans.
- Chat supervision and decision runs never move the arm at the same time; moves are bounded and supervised.
- Rerun is the main workspace, showing robot geometry, frames, camera streams, proposed paths, joint plots, and a capture timeline.
- A fresh checkout defaults to mock hardware; the lab deployment runs the real SO-101 with both Pi cameras behind Tailscale access.
Quickstart
bash
bun install
uv sync --extra dev
bun run build
bun run devWatch out
No license file, so reuse terms are unclear; needs Bun, Python 3.12, uv, and a WebGL2 or WebGPU browser, and real Jev calls require paid Vercel AI Gateway credits.
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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!
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typesafe's jev is fun! live demo you can play with: typesafe-demo.val.run
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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