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
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Speed: When tasks are independent and can be run concurrently to reduce total latency (e.g., verifying 5 different facts).
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Diversity: When you want multiple creative options (e.g., generate 5 different headlines).
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Reliability: When used in a "majority vote" pattern to reduce hallucinations (Self-Consistency).
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Aggregating Information: Researching a topic from multiple sources simultaneously.
Use Cases
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Batch Processing: Grading 100 student essays concurrently.
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Multi-Perspective Analysis: Asking a "Skeptic Agent", an "Optimist Agent", and a "Realist Agent" to review a plan simultaneously.
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Map-Reduce: Identifying key themes in 50 documents by summarizing them all in parallel (Map) and then synthesizing the summaries (Reduce).
Implementation Pattern
import asyncio
async def parallel_workflow(topic): # Define independent tasks tasks = [ research_agent.run(f"Research history of {topic}"), research_agent.run(f"Research economic impact of {topic}"), research_agent.run(f"Research cultural significance of {topic}") ]
# Execute all concurrently
# This takes as long as the slowest single task, not the sum of all tasks.
results = await asyncio.gather(*tasks)
# Synthesize results
final_report = synthesize_agent.run(
prompt="Combine these research findings into a report...",
input=results
)
return final_report
Troubleshooting
Problem Cause Fix
Race conditions Shared mutable state Use immutable message passing; collect results only in the aggregator
One slow task blocks completion No partial results Set a per-task timeout; return partial results after timeout
Rate limits hit with parallelization Too many concurrent API calls Add a semaphore (e.g., asyncio.Semaphore(10) ) to cap concurrency
Results aggregated in wrong order Non-deterministic completion order Tag each result with its task ID; sort before aggregating