Agent: Concurrent Orchestration in Semantic Kernel
Learn Microsoft AI presents an in-depth demo on concurrent orchestration in Semantic Kernel, showcasing how to run multiple AI agents in parallel and aggregate their results in .NET applications.
Agent: Concurrent Orchestration in Semantic Kernel
Presented by Learn Microsoft AI
Overview
This video introduces the concurrent pattern in the orchestration of AI agents using Microsoft’s Semantic Kernel framework. The presenter demonstrates how concurrent orchestration enables multiple agents to process tasks independently and aggregate their outputs, making AI applications more flexible and intelligent.
What’s Covered
- What is the Concurrent Pattern?
- Technique to enable multiple agents to address the same input simultaneously
- Aggregates diverse outputs for improved results
- Use Cases
- Brainstorming ideas with multiple agents
- Implementing ensemble reasoning
- Building voting systems for decision making
- Hands-on Demo
- Coding demonstration using .NET and Semantic Kernel
- Running multiple AI agents in parallel
- Collecting and combining agent outputs
Technical Highlights
- Use of Semantic Kernel for orchestrating agents
- .NET implementation patterns
- Support for multiple agent workflow scenarios
- Aggregation strategies for synthesizing agent responses
Example Scenario
Need to brainstorm product ideas? The concurrent pattern lets several AI agents generate their own unique ideas in parallel, then aggregates them for richer, more creative output.
Resources
- Semantic Kernel GitHub
- Code samples and further reading on author’s GitHub
About the Author
- Learn Microsoft AI
- YouTube Channel
For more examples and detailed walkthroughs, watch the full video or explore additional demos on the author’s channel.