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New Mode Launched by MuleRun for Personal AI Assists: Affordable Cloud-Based Handling of Complex Tasks

New Mode Launched by MuleRun for Personal AI Assists: Affordable Cloud-Based Handling of Complex Tasks

August 21, 2026
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These days, as AI agents become increasingly widespread, a personal AI assistant named MuleRun (MuleRun) that emphasizes self-evolution and zero entry barriers has captured significant attention within the industry. As its name implies, it combines the efficiency of a horse with the cost-effectiveness of a donkey, offering users reliable, affordable, and highly durable cloud-based digital labor solutions.

Unlike OpenClaw, which demands complex local setup, Mule’s greatest advantage is its accessibility — users can start using it simply by opening a web browser. It functions in two distinct modes, accommodating everything from long-term monitoring to immediate tasks.

Computer Mode: This function acts as a digital employee that remains continuously connected to the cloud and retains long-term memory. It not only handles tasks requiring ongoing oversight but also learns users’ work patterns and proactively updates them on progress.

Super Agent Mode: Comparable to “Taobao in the world of AI,” this mode is designed for completing one-time tasks. Whether users need code writing, website development, or PPT creation, they only have to pay based on their specific requirements and can discontinue use afterward.

The emergence of MuleRun not only lowers the barrier for ordinary people to access AI capabilities but also drives new growth opportunities across related industries. Currently available globally through major cloud service providers, its high-concurrency task processing capability is continuously increasing demand for computing power rentals and cloud services.

As this digital worker gradually expands into various sectors, development of AI applications tailored to specific industries is also expected to accelerate. From e-commerce operations to financial analysis, when AI can handle demanding tasks at low cost and with consistent reliability, the overall digital intelligence efficiency of society will see a significant improvement.

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