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.openpublishing.redirection.ai.json

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docfx.json

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docs/ai/conceptual/agents.md

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---
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title: Agents
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description: Introduction to agents
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author: luisquintanilla
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ms.author: luquinta
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ms.date: 10/01/2025
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ms.topic: concept-article
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---
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# Agents
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This article introduces the core concepts behind agents, why they matter, and how they fit into workflows, setting you up to get started building agents in .NET.
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## What are agents?
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**Agents are systems that accomplish objectives.**
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![Components of an agent](../media/agents/agent-components.png)
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Agents become more capable when equipped with the following:
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- **Reasoning and decision-making**: Powered by LLMs, search algorithms, or planning and decision-making systems.
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- **Tool usage**: Access to Model Context Protocol (MCP) servers, code execution, and external APIs.
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- **Context awareness**: Informed by chat history, threads, vector stores, enterprise data, or knowledge graphs.
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These capabilities allow agents to operate more autonomously, adaptively, and intelligently.
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## What are workflows?
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As objectives grow in complexity, they need to be broken down into manageable steps. That's where workflows come in.
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**Workflows define the sequence of steps required to achieve an objective.**
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Imagine you're launching a new feature on your business website. If it's a simple update, you might go from idea to production in a few hours. But for more complex initiatives, the process might include:
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- Requirement gathering
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- Design and architecture
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- Implementation
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- Testing
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- Deployment
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A few important observations:
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- Each step might contain subtasks.
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- Different specialists might own different phases.
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- Progress isn’t always linear. Bugs found during testing might send you back to implementation.
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- Success depends on planning, orchestration, and communication across stakeholders.
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### Agents + workflows = agentic workflows
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Workflows don't require agents, but agents can supercharge them.
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When agents are equipped with reasoning, tools, and context, they can optimize workflows.
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This is the foundation of multi-agent systems, where agents collaborate within workflows to achieve complex goals.
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### Workflow orchestration
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Agentic workflows can be orchestrated in a variety of ways. The following are a few of the most common:
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- [Sequential](#sequential)
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- [Concurrent](#concurrent)
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- [Handoff](#handoff)
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- [Group chat](#group-chat)
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#### Sequential
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Agents process tasks one after another, passing results forward.
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![Sequential agent orchestration: Task Input → Agent A → Agent B → Agent C → Final Output](../media/agents/sequential-workflow.png)
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#### Concurrent
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Agents work in parallel, each handling different aspects of the task.
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![Concurrent agent orchestration: Task Input → Agents A, B, C → Aggregate Results → Final Output](../media/agents/concurrent-workflow.png)
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#### Handoff
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Responsibility shifts from one agent to another based on conditions or outcomes.
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![Handoff orchestration: Task Input → Agent A Decision → Agent B or Agent A → Agent B Decision → Agent C or Agent B → Final Output](../media/agents/handoff-workflow.png)
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#### Group chat
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Agents collaborate in a shared conversation, exchanging insights in real-time.
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![Group chat orchestration: User and Agents A, B, C collaborate via GroupChat to produce final output](../media/agents/groupchat-workflow.png)
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## How can I get started building agents in .NET?
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The building blocks in <xref:Microsoft.Extensions.AI> and <xref:Microsoft.Extensions.VectorData> supply the foundations for agents by providing modular components for AI models, tools, and data.
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These components serve as the foundation for Microsoft Agent Framework.
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For more information, see [Microsoft Agent Framework](/agent-framework/overview/agent-framework-overview).

docs/ai/index.yml

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- text: Microsoft.Extensions.AI libraries
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- text: Microsoft Agent Framework
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url: /agent-framework/overview/agent-framework-overview?toc=/dotnet/ai/toc.json&bc=/dotnet/ai/toc.json
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- linkListType: get-started
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- text: Connect to and prompt an AI model
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docs/ai/toc.yml

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- name: Semantic Kernel
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href: microsoft-extensions-ai.md
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- name: Microsoft Agent Framework
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href: /agent-framework/overview/agent-framework-overview?toc=/dotnet/ai/toc.json&bc=/dotnet/ai/toc.json
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- name: How generative AI and LLMs work
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- name: Building agents in .NET
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href: conceptual/agents.md
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- name: Tokens
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- name: Embeddings

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