The Myth of AI-Powered Sisyphus (tawandamunongo.dev)

This essay argues that AI’s promise to “automate the tedious and amplify creativity” has an unexpected, structural cost: it multiplies what we can do faster than we can choose what to do. By collapsing barriers—time, boilerplate, basic skill—modern tools and LLMs make beginnings trivial and create an ever-growing backlog. The author casts this as a modern Sisyphus: the boulder is partly automated, the hill keeps rising, and the summit keeps moving. Rather than freeing us, AI expands the definition of productivity, turning saved minutes into new obligations and producing perpetual possibility instead of completion. For the AI/ML community this is a practical and design challenge. Technical progress (faster models, new frameworks, endless automation) creates tool churn and cognitive overload; the real constraint is human attention. Implications include rethinking success metrics beyond throughput, designing interfaces and models that respect finite attention (supporting prioritization, “enough,” and tasks that don’t scale), and studying human-AI interaction, cognitive load, and the societal effects of constant productivity claims. The essay calls for a shift from chasing infinite capability to cultivating chosen limits: build systems that help people decide what to stop doing, not just what to do next.