A browser agent that finds flights in seven seconds. A Claude session cut from a million tokens to 86,000 in one second. A WHERE clause that reads plain English. Vercel's safety reviewer. We are collecting what people built with Jev in its first days, and what they argued about, each in their own words. Nobody in these bylines is on eChai, and every entry links back to where it was posted.
Dan Shipper is the CEO of Every. Mike Taylor, its head of evals, fed Jev 37 documents with 21 questions each and got 777 judgments back in 0.7 seconds for about a quarter of a cent. Every's second test is the one independent number so far: on 12 passages with planted writing defects Jev caught six of seven where Fable 5.1 caught all seven, at 0.35 seconds a passage against 8.83, which is 25 times faster rather than the 200 in the launch claim.
Dan Shipper
3d
we almost never test new foundation models but we've been testing this for ~a week @every and it's pretty wild.
the kind of things that will be obviously indispensible in 6-12 months
it doesn't produce words as output, it produces probabilities. so it can efficiently act as a judge in cases where you'd need a Fable-level model—but in our testing was 25x faster and 600x lower priced
excellent vibe check by @hammer_mt on @every:
The funding, from the press release: a $40 million seed led by DCVC, where James Hardiman is a general partner. TypeSafe was founded in 2024 in San Francisco by Diogo Almeida, Erik Gafni and Sasha Sheng. Forbes reported the round at a $200 million valuation.
James Hardiman, DCVC, in Yahoo Finance
TypeSafe is approaching one of the biggest remaining challenges in AI: turning increasingly capable models into technology that developers can reliably build into products at scale.
Alex Duffy runs Goodstart Labs, which builds learning environments for agents and needs every action graded. On their sample Jev agreed with Fable 5.1 nine times in ten, at about 200 times lower grading cost and under half a second a call. Erik Gafni, named in the post, is one of TypeSafe's three co-founders.
Alex Duffy
3d
Awesome to see @EGafni & Diogo launch their first model Jev!
Verification is the bottleneck for building great AI learning environments. Jev is a welcome, unique, addition to our toolkit @goodstartlabs
Typed decisions,
probabilities for each option,
free output tokens!
On our sample:
• Jev agreed with Fable 5.1 nine times out of ten
• ~200× lower grading cost
• <0.5 seconds per grading call
That means more eyes on what agents are doing and what we’re teaching them.
More on how we’re using it to build game environments, experts to play them, and ensuring they teach the right things:
The second post in the launch thread, and the demo the whole week kept coming back to: Jev reading Doom's game state as text and picking the next move about ten times a second, at what TypeSafe puts at roughly $7 an hour. The lab says the input is a structured text state rather than the screen.
Diogo Almeida
3d
We love how this doomo doomonstrates real-time intelligence and what can be doone with code + AI!
~10 calls/sec = ~$7/hour
