Agent Frameworks

🎯 LangGraph vs Semantic Kernel

Community Vote — Which tool wins?

LangGraph

Tool A

Graph-based stateful orchestration runtime for agent loops.

Starting Price

Open-source + Cloud

Key Strengths

  • Graph-based state machine gives precise control over execution flow with conditional branching, loops, and cycles
  • Built-in checkpointing enables time-travel debugging, human-in-the-loop approval, and fault-tolerant resume from any step
  • Subgraph composition lets you build complex multi-agent systems from reusable, independently testable graph components
Full Review →

Semantic Kernel

Tool B

SDK for building AI agents with planners, memory, and connectors. - Enhanced AI-powered platform providing advanced capabilities for modern development and business workflows. Features comprehensive tooling, integrations, and scalable architecture designed for professional teams and enterprise environments.

Starting Price

Open-source

Key Strengths

  • Plugin system lets you expose existing C#/Python methods to LLMs with a single decorator — minimal refactoring needed
  • First-class .NET support with dependency injection, middleware patterns, and enterprise conventions C# teams already know
  • Azure OpenAI deep integration with managed identity, content safety filters, and enterprise deployment patterns baked in
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Which would you choose for...

Vote in each scenario below

Customer support agents

Data pipeline automation

Quick prototyping

Production deployment

Full Comparison →