From the original post
how to setup and use Jev in 10 minutes
from nothing to a call that returns a decision
1. get access
join the waitlist at typesafe, people report getting in within a day
don't want to wait, it's already hosted in two places:
→ vercel ai gateway as typesafe-ai/jev, no waitlist
→ cloudflare workers ai as typesafe/jev
2. install the skill so your agent writes the call correctly
npx skills add typesafe-ai/skills --skill typesafe-ai
on claude code it's two commands:
- claude plugin marketplace add typesafe-ai/skills
- claude plugin install typesafe@typesafe-ai
then in your prompt just say "use the typesafe skill"
3. learn the shape before you write a line
the body is a state and a map of questions. the state is your context, whatever you would have pasted into a prompt. the questions are typed
three types, that's the entire api:
→ Noul returns a raw 0 to 1
→ Choice picks one from up to 255 options you define
→ Score places it on a 2 to 10 level scale
every Choice and Score comes back with a confidence from 0 to 1
4. make the first call a real one
pick a decision already living in your code as an llm call that never writes text. the "which of these" one
how to do it:
- build the option list in your own code, not in the prompt
- send your existing context as the state, unchanged. don't rewrite it yet
- ask your question plus three more you're curious about, they run in parallel against the same state and output tokens are free
- log the answer, the confidence, and what your old call said
- leave the old call running. delete nothing on day one
5. put a limit on it before it touches anything
read confidence on every response, never just the answer
low limit for reading and sorting. 0.85+ for anything you cannot undo. everything under the limit falls through to the old call
that fallback is four lines, and it's the reason you can ship this on a tuesday instead of planning it for q4
the 10 minutes is real. the hour after is the actual work: you, a log of answers and confidences, deciding where your lines go
start in the playground in the console, and paste a real state from your own product, not the sample one
How Jev fits in the loop
- Agent collects runtime context or input state from external sources.
- Bounded decision options are formatted into Jev System One questions.
- Jev scores each candidate option and returns a probability for it.
- Deterministic code executes the selected action or routes to specialized models.
How to reproduce
- Read the author's original post on X at https://x.com/eng_khairallah1/status/2101696759382540369.
- Inspect the described workflow architecture and bounded decision points.
- Test Jev System One decision queries against the provided task context.
Why this build matters
Demonstrates real-world Jev Skills experimentation by @eng_khairallah1 with verified community reach of 9.8k views.
Limitations
- Implementation details are based on the author's public post on X.
- Performance figures and benchmarks are author-reported community claims.
- Production deployments may require custom calibration and policy thresholds.