TypeSafe founder Diogo Almeida, who previously worked on OpenAI's InstructGPT, told the Latent Space podcast that the AI world before Jev was "a tragedy": strong intelligence engines exist, but the interface for wiring them into real business processes is missing. He describes Jev as a System 1 or "large programmable" model trained with reinforcement learning for calibrated decisions (RLCD), so code can directly consume its choices, scores and probabilities and set thresholds for when to act or hand off to a human. He also criticises RLHF mode dropping for distorting calibration, argues specific value judgments should not be baked into a general model's底层 behaviour, and says he dislikes optimising for public leaderboards, adding that benchmark-use restrictions came from preview terms and will be revised.