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On OpenMausBot, Jev reads an incoming task and decides which bot to wake and which underlying LLM to assign it, working across the user's existing LLM subscriptions.
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The 1,978-point, 513-comment launch thread. The top comment calls the speed comparison misleading, since Jev only returns structured output, and disputes the cannot-hallucinate claim because a valid type can still hold a wrong value. Others note ordinary LLMs can already be forced into structured output.

The founder's launch post, around 76k likes, arguing that RLCD-trained decision models are a shorter path to economic value than chat models. Submitted separately to HN as item 49716682.
39M viewsSpeed 20-200x fasterCost 40-400x cheaper
A video demo pairs json-render with Jev to render generative UI components in milliseconds, using the viewer's own components, actions, and design system.

A video demo of copy and paste made 'smart' using Jev from TypeSafe, with no further detail on the mechanism given in the post text.

A demo breaking down 724 live ads from 37 brands in 40 seconds for 9 cents, covering hook, format, offer, CTA, funnel stage and landing-page mismatch for each ad.
1.1M viewsSpeed 724 ads/40sCost 9 cents

A video demo has Jev read 586 pages of a site in 45.1 seconds and rebuild the internal link map, placing 584 links and refusing 139 pages where nothing fit, for $0.21 total. In the same time, Claude Opus 5 processed only 21 of the same pages for $1.43.
827k viewsPages read 586 in 45.1sCost $0.21