A developer shows Jev clearing a 2M ticket queue in under 20 seconds using just three booleans (spam, urgent, needs human), costing only $0.21.
IT SORTED TWO MILLION TICKETS AND NEVER WROTE A SINGLE WORD i handed jev 2,000,000 support tickets. the queue hit zero in under 20 seconds. it cost 21 cents. the whole schema is three booleans. is this spam, is it urgent, does it need a human. that is the entire output. words
The author shares a Jev usage insight: it seemed tricky at first, but clicked when framed as 'not letting the AI write text.' Using inquiry handling as an example, the conventional approach dumps everything on GPT or Claude to analyze, while Jev takes a different approach.
The prototype uses AI to estimate hesitation or interest from cursor back-and-forth movements or lingering before clicking, observing customer demeanor and supplementing explanations or suggesting comparisons.
The author built an e-commerce real-time customer service demo using Jev and gpt-live-1, which instantly suggests recommended products based on the user's speech during a conversation, delivering a great experience.
