A research paper proposes a two-pass decomposition approach for multimodal review tasks, where the first pass transcribes the source and the second pass reviews the transcript. This approach improves faithfulness and coverage, but introduces potential failure modes such as running out of room or confabulation. This matters to people building or operating AI agents because it suggests a potential solution to the limitations of single-pass multimodal models.