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One question (please take in account that I am no more than a dabbler in this field) - you conclude your piece with ... the nature of the problem slowly changes over time and prediction quality deteriorates.

Isn't this a problem anyway, even with models based on much larger datasets?

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You are right, data/concept drift affects both approaches.

What I meant to say was that retraining your model might not fix that if you baked strong assumptions into it. I edited the blog post to make it clearer.

With small datasets you need to know how the concept drifts well enough to model it or model the failure modes. That's half the game in my opinion.

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