Both Semantic Kernel and AutoGen offer unique capabilities for working with LLMs, and the choice between them depends on the specific requirements of your project. Semantic Kernel is about creating single AI agents and equipping them with the tools to do tasks, while AutoGen is about managing complicated workflows that involve multiple agents, each with different skills and functions. Both technologies can work together; for example, you can use Semantic Kernel to give tools (via plugins) to agents made in AutoGen. This lets AutoGen agents access real-time information and communicate more efficiently.