Semantic Kernel vs Agent Framework

Executive Summary

Microsoft Agent Framework is the unified successor to both Semantic Kernel and AutoGen, created by the same teams. It combines AutoGen's multi-agent patterns with Semantic Kernel's enterprise features while introducing new capabilities.

✓ Semantic Kernel Status

• v1.0 GA (Production Ready)
• Supports .NET, Python, Java
• Enterprise-grade features
• Microsoft Support available

⚡ Agent Framework Status

• Public Preview (Oct 2025)
• GA expected Q1 2026
• Supports .NET & Python
• Next-gen architecture

Feature Comparison Matrix

Feature	Semantic Kernel	Agent Framework
Maturity	v1.0 GA (Production)	Public Preview
Core Abstraction	Kernel + Agent classes	AIAgent (unified)
Agent Types	ChatCompletionAgent, OpenAIAssistantAgent, AzureAIAgent	ChatClientAgent (unified)
Tool Registration	[KernelFunction] + Plugin + Kernel	Direct function registration
Thread Management	Manual type-specific creation	agent.GetNewThread()
Multi-Agent	Agent Framework (preview)	Native workflows + orchestration
Workflows	Process Framework (preview)	Graph-based workflows (core)
State Management	Thread-based	Checkpointing + durability
MCP Support	Via connectors	Native first-class
Microsoft.Extensions.AI	Collaboration partner	Built on top of it
Boilerplate Code	Higher	Significantly reduced
Performance	Good	Optimized (better memory)

Architectural Differences

Semantic Kernel Architecture

graph TB subgraph SK["Semantic Kernel"] Kernel["Kernel
(Core Orchestrator)"] Plugins["Plugins
(KernelFunction)"] Memory["Memory
(Vector Stores)"] Planner["Planner
(Multi-step)"] end subgraph Agents["Agent Types"] CCA["ChatCompletionAgent"] OAA["OpenAIAssistantAgent"] AZA["AzureAIAgent"] end subgraph Services["AI Services"] OpenAI["OpenAI"] Azure["Azure OpenAI"] Foundry["Azure AI Foundry"] end Kernel --> Plugins Kernel --> Memory Kernel --> Planner CCA --> Kernel OAA --> Kernel AZA --> Kernel CCA --> OpenAI OAA --> OpenAI AZA --> Foundry style SK fill:#1e3a5f style Agents fill:#2d5016 style Services fill:#4a1e3a

Agent Framework Architecture

graph TB subgraph AF["Agent Framework"] AIAgent["AIAgent
(Unified Base)"] Thread["AgentThread
(State Management)"] Context["Context Provider
(Memory)"] Middleware["Middleware
(Filters)"] end subgraph Impl["Implementation"] ChatClient["ChatClientAgent
(IChatClient)"] Tools["Tools
(Direct Functions)"] MCP["MCP Servers
(Native)"] end subgraph WF["Workflows"] Graph["Graph-based
Workflows"] Checkpoint["Checkpointing"] Orchestration["Multi-Agent
Orchestration"] end subgraph Base["Foundation"] ExtAI["Microsoft.Extensions.AI
(IChatClient)"] end AIAgent --> Thread AIAgent --> Context AIAgent --> Middleware ChatClient --> AIAgent ChatClient --> Tools ChatClient --> MCP Graph --> AIAgent Checkpoint --> Thread Orchestration --> Graph ChatClient --> ExtAI style AF fill:#1e3a5f style Impl fill:#2d5016 style WF fill:#4a1e3a style Base fill:#5a3a1e

Migration Path

sequenceDiagram participant SK as Semantic Kernel participant AF as Agent Framework participant Prod as Production Note over SK: v1.0 GA
Production Ready SK->>SK: Continue development SK->>AF: Migration guide available Note over AF: Public Preview
(Oct 2025) AF->>AF: Feature additions Note over AF: GA Release
(Q1 2026) AF->>Prod: Enterprise adoption Note over SK,AF: Both supported
during transition SK-->>AF: Gradual migration Note over AF: Becomes primary
framework

Key Migration Changes

Before (Semantic Kernel)

Kernel kernel = Kernel
  .AddOpenAIChatClient(modelId, apiKey)
  .Build();

ChatCompletionAgent agent = new() {
  Instructions = "You are helpful",
  Kernel = kernel
};

AgentThread thread = 
  new OpenAIAssistantAgentThread(client);

await foreach (var result in 
  agent.InvokeAsync(input, thread)) {
  Console.WriteLine(result.Message);
}

After (Agent Framework)

AIAgent agent = chatClient.CreateAIAgent(
  instructions: "You are helpful"
);

AgentThread thread = agent.GetNewThread();

AgentRunResponse response = 
  await agent.RunAsync(input, thread);

Console.WriteLine(response.Text);

Workflow Capabilities

Agent Framework introduces graph-based workflows for explicit multi-agent orchestration, addressing limitations of single agents handling complex tasks.

graph LR subgraph Workflow["Multi-Agent Workflow"] Start([User Request]) Router{Router
Agent} Research[Research
Agent] Analysis[Analysis
Agent] Writer[Writer
Agent] Human{Human
Review} End([Response]) end Start --> Router Router -->|"Query"| Research Router -->|"Data"| Analysis Research --> Writer Analysis --> Writer Writer --> Human Human -->|"Approve"| End Human -->|"Revise"| Writer style Start fill:#2d5016 style End fill:#2d5016 style Router fill:#4a1e3a style Human fill:#5a3a1e

Modularity

Break workflows into reusable components

Checkpointing

Save/resume long-running processes

Type Safety

Strong typing prevents runtime errors

.NET AI Ecosystem Updates (2025)

Microsoft.Extensions.AI

Core .NET libraries providing unified abstractions for AI services, developed in collaboration with Semantic Kernel team.

Unified API: Consistent abstractions across AI providers
Flexibility: Provider-agnostic integration
IChatClient: Standard interface for chat completions
Middleware: Telemetry, caching, function calling

.NET 9 & 10 AI Features

.NET 9 (Released)

• Microsoft.Extensions.AI integration
• AI evaluation libraries
• Vector store connectors
• Enhanced telemetry

.NET 10 (Preview)

• Agent Framework integration
• MCP first-class support
• Agentic workflow templates
• Multi-language orchestration

Azure AI Foundry Integration

Foundry Agent Service: Hosted agent runtime with durability
Agent 365: Unified registry, access control, visualization
DevUI: Browser-based agent testing and debugging
Durable Task Extension: Bulletproof agents with auto-scaling

Roadmap & Future Direction

gantt title Microsoft AI Agent Framework Timeline dateFormat YYYY-MM section Semantic Kernel v1.0 GA Release :done, 2024-06, 2024-12 Continued Support :active, 2024-12, 2026-12 section Agent Framework Public Preview :done, 2025-10, 2025-11 Feature Additions :active, 2025-11, 2026-01 GA Release :milestone, 2026-01, 0d Enterprise Adoption :2026-01, 2026-06 section Ecosystem .NET 9 AI Features :done, 2024-11, 2025-01 .NET 10 Preview :active, 2025-11, 2026-05 Azure Foundry GA :2025-11, 2026-03

Semantic Kernel Future

• Maintained for existing applications
• Security updates and bug fixes
• No major new features
• Migration tools to Agent Framework
• Compatibility layer support

Agent Framework Future

• Primary framework going forward
• Advanced orchestration patterns
• Enhanced observability
• More MCP integrations
• Visual workflow designers

Recommendations

✓ Use Semantic Kernel If:

• You need production-ready, GA-supported framework now
• Your application is already built on Semantic Kernel
• You require Microsoft enterprise support contracts
• You need Java support (Agent Framework is .NET/Python only)
• You prefer stability over cutting-edge features

⚡ Use Agent Framework If:

• You're starting a new project and can wait for GA (Q1 2026)
• You need advanced multi-agent orchestration patterns
• You want graph-based workflows with checkpointing
• You require native MCP server integration
• You want simplified API with less boilerplate
• You're building on Azure AI Foundry

⚠ Hybrid Approach:

For organizations with existing Semantic Kernel investments:

• Continue using SK for production workloads
• Prototype new features with Agent Framework
• Plan phased migration post-GA (Q1 2026)
• Use migration guides for gradual transition
• Leverage compatibility layers (KernelFunction → Agent tools)

Industry Trends (2025)

• Stateful graphs replacing linear chains (LangGraph influence)
• Human-in-the-loop becoming standard requirement
• Enterprise governance driving framework selection
• MCP adoption for standardized tool integration
• Observability and debugging tools critical for production