Is AI helping you to do work, or just to do stuff? (coyotetracks.org)

A recent exploration of AI's efficacy in enhancing productivity, particularly focusing on the emergence of OpenClaw—a personal assistant AI—raises significant questions within the AI/ML community. The discussion highlights the balance between genuine productivity and simply "doing stuff." OpenClaw, which automates tasks from managing calendars to sending messages, has gained traction among users for its promise of efficiency, but this raises concerns over security risks and the potential for misuse. Critics argue that while these AI tools are revolutionary, they often lead users to mistake the process of managing automation for actual work accomplished. The critique extends to the broader implications of large language models (LLMs) and their limitations, emphasizing that they often generate output that reflects a statistical median rather than innovative solutions. The author underscores a fundamental flaw in viewing LLMs as tools that can easily replace traditional programming and app development, suggesting that the complexity and creativity involved in such tasks are often lost in the pursuit of automation. As AI tools like OpenClaw develop, the challenge remains for users to discern between genuine productivity and time spent on tasks that provide an illusion of progress without yielding substantial results.