OpenAI has a Muse problem

The current wave of consumer-friendly AI agents, exemplified by Meta’s Muse and OpenAI’s Dots, marks a transition from theoretical ideation to functional deployment. These agents operate as AI models wrapped in a harness that allows them to navigate web browsers and execute multi-step tasks independently. While both companies utilize similar technical architectures, their market strategies diverge significantly: Meta leverages its massive distribution and consumer-product expertise to offer a free, accessible tool, whereas OpenAI targets enterprise users with high-subscription tiers and specialized capabilities. This race toward agentic computing raises critical concerns regarding data privacy, security, and the potential for "corrupt butler" monetization, where agents prioritize paid merchant recommendations over user needs. Despite the industry’s push for these cute, disarming mascots, the technology remains brittle, struggling to reliably handle complex, real-world consumer tasks without significant user intervention.