Parallelization

Parallelization allows an agentic system to perform multiple independent operations simultaneously. This is commonly used in distinct flavors: "Sectioning" (breaking a large task into independent chunks to process in parallel) and "Voting" (running the same task multiple times to get diverse outputs for consensus or increasing quality).

When to Use

• Speed: When tasks are independent and can be run concurrently to reduce total latency (e.g., verifying 5 different facts).
• Diversity: When you want multiple creative options (e.g., generate 5 different headlines).
• Reliability: When used in a "majority vote" pattern to reduce hallucinations (Self-Consistency).
• Aggregating Information: Researching a topic from multiple sources simultaneously.

Use Cases

• Batch Processing: Grading 100 student essays concurrently.
• Multi-Perspective Analysis: Asking a "Skeptic Agent", an "Optimist Agent", and a "Realist Agent" to review a plan simultaneously.
• Map-Reduce: Identifying key themes in 50 documents by summarizing them all in parallel (Map) and then synthesizing the summaries (Reduce).

Implementation Pattern