AI Agents Take On Real-World Tasks as Meta and OpenAI Launch Browsing Assistants
Meta's free Muse app and OpenAI's $100-a-month dots mark a new era of AI agents capable of booking tables, applying for jobs, and matching prices online.
The landscape of artificial intelligence is shifting from conversational text boxes to autonomous software agents capable of executing tasks on a user's behalf. While traditional chatbots answer questions, modern agents operate with virtual browsers and desktop environments to perform complex multi-step actions. Leading this transition are Meta's free mobile app Muse, which recently became the most downloaded phone app, and OpenAI's dots, an agent feature available under the $100 monthly ChatGPT Pro 100 tier. Anthropic also joined the space recently by announcing tests for its own agent, named Duet.
Unlike earlier virtual assistants from tech giants like Google, Apple, and Amazon—which often struggled with speed and limited functionality—today's AI agents operate continuously in the background. Users can connect personal applications such as Gmail, though caution is recommended regarding data privacy, as personal information processed by these assistants may be reviewed by companies to refine their underlying models.
Real-world testing shows practical automation
In hands-on testing across several routine digital tasks, AI agents demonstrated varying degrees of capability and reliability. One prominent challenge was securing reservations at high-demand venues, such as Sun Moon Studio, a 12-seat Michelin-starred restaurant in Oakland, California. While both assistants initially struggled, OpenAI's dots eventually monitored availability and reached a booking confirmation screen for a late November table.
Other tests highlighted key functional differences between the systems:
- Location-based triggers: Asked to deliver a custom workout plan upon entering a local rock climbing gym, Muse successfully triggered a message upon arrival. Dots declined the task because it lacks real-time location tracking features.
- Automated applications: When instructed to monitor a caregiver job site and submit tailored recommendations for a nanny, Muse submitted eight applications while the user loaded groceries, yielding two parent responses within an hour. Dots ran into browser glitches and failed to complete the task.
- Daily scheduling: Both agents successfully delivered 7:00 a.m. meal recommendations for family dinners and toddler lunches based on existing refrigerator inventory.
- Price negotiations: Both assistants identified a set of top-rated Michelin tires priced $80 cheaper online and filled out web forms at a local tire store to request a price match, which the store confirmed via email shortly after.
Overall, Meta's free Muse app proved more capable in daily consumer scenarios compared to dots, which faced browser instability and higher costs.
What it means for developers
The emergence of consumer agents underscores a massive transition toward background execution, persistent memory, and automated browser interaction. OpenAI's head of enterprise product, Alexander Embiricos, explained in an interview that dots was originally targeted at complex business workflows, such as assisting freelancers in managing operations, rather than lightweight personal chores. Embiricos noted that OpenAI expects dots to eventually become free after testing the technology with paid users.
Building software for this new paradigm requires developers to orchestrate reasoning, web browsing, and tool usage across diverse model providers. For engineers evaluating or integrating these capabilities into their applications, developers can try top AI models cheaply through one API at https://apixoai.online to experiment across models like Claude, GPT, Gemini, and DeepSeek without managing multiple enterprise subscriptions.
As agentic systems evolve from simple text processing to acting on web forms, location signals, and live scheduling, software engineers must prioritize robust error handling and strict data isolation. Because agent platforms rely on deep access to user data, establishing secure API integrations will remain critical as these autonomous tools become mainstream infrastructure.
Source: Put your AI agents to work with these 5 killer tasks — Indian Express AI. Written by the Apixo team from that report.
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