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Implement multi-head attention from scratch with a KV cache for decoding, then extend it to grouped-query attention.

The 2026 ML coding round has moved past plain multi-head attention: labs now chain it into KV-cached decoding and GQA in a single sitting. The locked answer walks the full NumPy implementation, the one equivalence check that proves your cache is correct, and the reshape bugs that silently corrupt attention.

Updated Aug 2026 · Grounded in real GenAI, LLM, and AI/ML engineering interview loops and written to a senior-engineer editorial bar.

The 2026 ML coding round has moved past plain multi-head attention: labs now chain it into KV-cached decoding and GQA in a single sitting. The locked answer walks the full NumPy implementation, the one equivalence check that proves your cache is correct, and the reshape bugs that silently corrupt attention.

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