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Credits of the image to Anthropic

Overview

Parallelization allows LLMs to work simultaneously on a task and have their outputs aggregated programmatically. This workflow manifests in two key variations:
  • Sectioning: Breaking a task into independent subtasks run in parallel
  • Voting: Running the same task multiple times to get diverse outputs

Examples in Latitude

Sectioning

Content Generation with Guardrails

Voting

Code Security Review
This pattern is particularly effective when you need either speed (through parallelization) or confidence (through multiple expert opinions), and when the cost of additional LLM calls is justified by the improved quality or reduced risk.