Optimizing Personal AI Workflows: Avoid Over-Optimization, Embrace Experimentation
brandon_galang · x · 2026-08-29
The author shares observations from an internal AI workflow show-and-tell at Vercel, noting that many get stuck 'reinventing the wheel' without landing on a working setup. While it's easy to over-optimize, this process is part of learning. The key tip is to schedule dedicated experimentation time. AI workflows are multidimensional; a setup that doesn't work today might become incredibly effective tomorrow with a small tweak or a new model/tool release.
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