While standard LLMs are still streaming the first JSON response, Jev has already resolved 13 support tickets across 4 structured criteria. Instant classification beats slow text generation.
Bonus 2: 13 support tickets in parallel by @0xnoonez While standard LLMs are still streaming the first JSON response, Jev has already resolved 13 support tickets across 4 structured criteria. Instant classification beats slow text generation every time.
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.
