TL;DR: Meta’s Muse, OpenAI’s Dots and Uber’s driver assistant share one bet: the agent speaks first. That moves the hard problem from what to answer to when to interrupt, on which channel, and with what offer. Classic ML and new decision models can solve it. Three launches, one pattern Meta Muse (Sept 8). A personal agent that books, emails and keeps working with the app closed. It remembers details, makes unprompted suggestions and checks in for approval, in its own app and in WhatsApp. OpenAI Dots (Sept 29). Always-on agents that run “proactive research,” read-only monitoring of your apps, to catch a forgotten invoice or a bug in Slack. They reach you in ChatGPT, Slack and Teams, with text and voice coming. Uber’s driver assistant. It turns live marketplace signals into advice. In a recent talk, Uber’s product team described a driver idle for 33 minutes being pointed to a better zone, with evidence. Their principles: stay “always on the driver’s side,” surface opportunities proactively, and measure whether drivers acted. A hands-free voice version was announced Sept 24. From pull to push Chatbots were a pull interface: the user chose the moment, the channel and the question. Proactive agents invert that. Interrupt too often and users mute you. Interrupt too late and the surge has ended or the invoice is overdue. Pick the wrong channel and a good message fails. The LLM can write the message; it is the wrong tool to decide whether to send it. The rule: value must beat interruption cost Every proactive message is a bet. Send only when its expected value to the user exceeds t
Source: MarkTechPost