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What do the feed-forward (MLP) layers in a transformer do, and why are they most of the parameters?

Everyone fixates on attention, but the feed-forward layers hold most of a transformer's weights and do much of the per-token 'knowledge' work. The signal is knowing what the FFN computes and why it dominates the parameter count.

Updated Aug 2026 · Grounded in real Applied AI Engineer interview loops and written to a senior-engineer editorial bar.

Everyone fixates on attention, but the feed-forward layers hold most of a transformer's weights and do much of the per-token 'knowledge' work. The signal is knowing what the FFN computes and why it dominates the parameter count.

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