AI tools significantly accelerate task completion, with some reporting efficiency gains of 2 to 100 times. This increased productivity, however, has not eliminated burnout as might be expected. Instead, it has created a new challenge where individuals use their newfound capacity to engage in an excessive number of side projects.
Many tech professionals, previously constrained by time, now find themselves with the ability to pursue numerous shelved ideas. This leads to a proliferation of "proof of concept" projects, each becoming an open loop and a new responsibility. This phenomenon is described as "make-work," where work is created chiefly to keep one busy, despite the initial enjoyment it might bring.
The author experienced this firsthand, accumulating around 40 side projects, which eventually led to feelings of burnout. The human capacity for sustained high-speed operation is limited, and attempting to manage too many concurrent projects, even with AI assistance, results in mental fatigue and stress. This contradicts the initial expectation that AI would reduce workload and burnout.
The core issue is how AI is utilized. Instead of using AI to expand the quantity of tasks or projects (horizontal expansion), a more effective strategy involves using AI to deepen engagement and progress on a smaller, more focused set of initiatives. This approach aligns with principles of essentialism, advocating for doing "less, but better" in an AI-augmented environment.
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The increased efficiency provided by AI tools can paradoxically lead to burnout, as individuals use the extra capacity to take on too many side projects. This phenomenon, termed "make-work," results from attempting to do "all the things" rather than focusing on fewer, more impactful tasks. The author suggests that AI should be used to deepen focus on existing projects, not to expand the number of commitments.