Semantic Kernel vs Strands (2026)
Updated March 10, 2026
Overview
Semantic Kernel is Microsoft's enterprise SDK for integrating AI into applications. It provides planners for multi-step task execution, plugin architectures for tool use, memory systems, and connectors for all major LLM providers. Available in C#, Python, and Java, Semantic Kernel is designed for enterprise .NET shops building AI-powered features into existing applications.
AWS-backed open-source agentic SDK for building AI agents
Key features
Core capabilities each platform advertises.
- Enterprise AI orchestration by Microsoft
- C# and Python SDKs
- Plugin architecture for tools
- Memory and planning capabilities
- Azure and Microsoft 365 integration
StrandsStrengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Free open-source
- Microsoft-backed
- Multi-language
Cons
- Learning curve
- Microsoft focus
StrandsPros
- Production-proven by AWS teams (Amazon Q, AWS Glue)
- True provider-agnostic support for 8+ LLM providers
- Comprehensive multi-agent orchestration with A2A protocol
- Rich AWS ecosystem integration
- Open-source with active development
Cons
- Relatively new framework (launched 2025)
- AWS ecosystem bias in design and tooling
- Variable costs depending on chosen providers
Semantic Kernel or Strands — which should you choose?
Choose Semantic Kernel if you wantChoose if you want
- Enterprise AI on Microsoft stack
- Copilot-style applications
- Integrating AI into .NET applications
- Microsoft 365 automation
- Enterprise workflow orchestration
Choose Strands if you wantChoose if you want
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