Parallel Tool Calling
Master concurrent tool execution to build faster, more efficient AI agents
Your Progress
0 / 5 completedThe Decision Framework
Not every task benefits from parallel execution. The key is identifying independence — can operations run without waiting for each other?
Quick Decision Tree
1
Are the tools independent?
✓ Yes → Continue to step 2
✗ No → Use sequential execution
✗ No → Use sequential execution
2
Is the workload I/O bound?
✓ Yes (API calls, database) → Continue to step 3
✗ No (heavy CPU work) → Consider parallelism carefully
✗ No (heavy CPU work) → Consider parallelism carefully
3
Do you have multiple tasks?
✓ Yes (3+ tools) → Use parallel execution
✗ No (1-2 tools) → Overhead might not be worth it
✗ No (1-2 tools) → Overhead might not be worth it
✅
Result: Use Parallel Execution!
Your tasks are independent, I/O bound, and numerous enough to benefit from parallelism.
Interactive: Scenario Analyzer
Click on scenarios to see whether they benefit from parallel execution
Data Aggregation
Fetch data from multiple sources for a unified view
Sequential Workflow
Each step depends on the previous result
Multi-Source Search
Search across multiple databases or APIs
Batch File Processing
Process multiple files independently
Chained Dependencies
Each operation uses output from previous
Multiple Validation Checks
Run several independent validation rules
Common Parallel Patterns
📊
Data Aggregation
Fetch data from multiple sources and combine
✓ Highly parallelizable
🔍
Multi-Source Search
Search across different databases/APIs
✓ Highly parallelizable
✅
Validation Checks
Run independent validation rules
✓ Highly parallelizable
📁
Batch Processing
Process multiple files/items independently
✓ Highly parallelizable