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In terms of absolute progress (e.g. towards finishing a feature or MVP) I think it it could have to do with a usual underestimation (optimism) for timelines.

I'm using Cursor mostly for exploratory/weekend projects. I usually opt for stacks/libraries I'm less familiar with, so I think there's some optimism/uncertainty to account for there.

I think there's another aspect to progress involving learning/becoming fluent in a codebase. When I build something from scratch, I become the expert, so familiar that later features become very easy/obvious to implement.

I haven't had this experience when I take a heavily agent-driven approach. I'm steering, but I'm not learning much. The more I progress, the harder new features feel to implement.

I don't think this is unique to working with AI. I guess the takeaway is that attention and familiarity matter.



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