Microsoft AI Landscape: Semantic Kernel vs. Agent Framework

Executive Summary

The relationship between Semantic Kernel (SK) and the Microsoft Agent Framework is not competitive but evolutionary and hierarchical.

Semantic Kernel is the foundational integration layer (SDK) for bringing LLMs into code.
Microsoft Agent Framework (Preview Oct 2025) is the orchestration platform that unifies SK and AutoGen to build complex, multi-agent autonomous systems.

graph TD subgraph "Application Layer" A["Enterprise App"] --> B["Agent Framework"] end subgraph "Microsoft Agent Framework (The Unifier)" B --> C["Multi-Agent Orchestration"] B --> D["State Management"] B --> E["Workflow Graphs"] end subgraph "Foundational Layer (Semantic Kernel)" C & D & E --> F["Semantic Kernel Core"] F --> G[Connectors] F --> H["Plugins/Skills"] F --> I["Memory/Vector Store"] end subgraph "AI Models" G --> J["Azure OpenAI"] G --> K["Hugging Face"] G --> L["SLMs (ONNX)"] end style B fill:#1e3a8a,stroke:#3b82f6,stroke-width:2px style F fill:#581c87,stroke:#a855f7,stroke-width:2px

Comparison Matrix

Feature	Semantic Kernel (SK)	Microsoft Agent Framework
Primary Role	Integration SDK (LLM Orchestrator)	Multi-Agent System Platform
Core Abstraction	Kernel, Function, Plugin, Memory	Agent, Group Chat, Workflow, Thread
Architecture	Stateless (mostly), Request/Response	Stateful, Event-Driven, Long-running
Multi-Agent	Basic (manual coordination)	Native (Group Chat, Handoffs, Magnetic)
Best Use Case	Copilots, RAG, Single-task Automation	Complex Workflows, Autonomous Teams
Origin	Microsoft Research (C# First)	Unification of SK & AutoGen

Semantic Kernel: The Foundation

Semantic Kernel remains the "metal" closest to the LLM. It provides the essential plumbing for enterprise AI: connectors, memory, and plugin management.

Core Components

Kernel: Dependency injection container for AI.
Plugins: Native code or prompts wrapped as functions.
Connectors: Abstractions for OpenAI, HuggingFace, etc.
Filters: Enterprise-grade interceptors for safety/PII.

Recent Updates (v1.x+)

Process Framework: New way to define linear steps.
Vector Store Abstractions: Standardized memory access.
OpenTelemetry: Native observability support.

Microsoft Agent Framework: The Future

Announced in Public Preview (Oct 2025), this framework addresses the complexity of coordinating multiple agents. It brings the "magical" orchestration of AutoGen into a stable, enterprise-ready .NET/Python environment.

sequenceDiagram participant User participant Orchestrator participant CoderAgent participant ReviewerAgent User->>Orchestrator: "Build a snake game in Python" Orchestrator->>CoderAgent: Assign Task CoderAgent->>Orchestrator: Submit Code Orchestrator->>ReviewerAgent: Request Review ReviewerAgent-->>CoderAgent: "Bug found in line 10" CoderAgent->>Orchestrator: Submit Fix Orchestrator->>User: "Here is the verified game"

Key Innovations

Unified Runtime: Runs agents built with SK or AutoGen concepts in a single environment.

Magnetic Orchestration: Agents automatically "attract" relevant tasks from a shared pool based on their capabilities.

Human-in-the-loop: Native support for pausing workflows to get user approval or input.

.NET Ecosystem Updates (2025)

The entire platform is reorienting around AI.

Microsoft.Extensions.AI

A new standard library in .NET 9/10. Provides a unified interface (IChatClient, IEmbeddingGenerator) for ANY AI provider.

Microsoft Orleans

The "Virtual Actor" model is being repurposed for Agentic AI. Ideal for hosting millions of stateful, distributed agents.

Vector Data

Microsoft.Extensions.VectorData standardizes how .NET apps talk to vector DBs (Qdrant, Pinecone, Redis).

Roadmap 2025-2026

Q1 2025 (Past)

Semantic Kernel Agent Framework GA.

Oct 2025 (Recent)

Microsoft Agent Framework Public Preview. Unification of SK and AutoGen concepts.

Q1 2026 (Upcoming)

Microsoft Agent Framework General Availability (GA). Full production SLAs and Azure integration.