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A solo experiment using a small-scale AI model has challenged conventional wisdom in directory submission. Instead of blindly submitting to high-authority, generic directories, the AI, trained on historical referrer data, prioritized niche directories with surprisingly positive results. The model analyzed factors like domain metrics, outbound link ratios, and indexation status to categorize directories as ‘worthwhile’ or ‘meh’. The findings indicated that smaller, specialized directories generated more genuine clicks than their larger, more general counterparts. The experiment also highlighted the effectiveness of startup launch platforms in driving initial traffic and accelerating page crawling. The individual even incorporated data from a commercial ‘done-for-you’ service into the model to further refine its accuracy. This novel approach, documented on Reddit (https://old.reddit.com/r/artificial/comments/1mtvgm2/used_smallscale_al_to_rank_good_vs_garbage/), demonstrates the potential of AI in optimizing seemingly mundane SEO tasks and uncovering unexpected traffic sources.