AB-100: Build & Configure Agents

Build & Configure Agents is one of the skill areas tested on the Agentic AI Business Solutions Architect (AB-100) exam. Below are free AB-100 practice questions with worked answers and a concept diagram — each with a plain-language explanation. Practice the first 10 questions of AB-100 free, no signup.

The concept, in one picture

Concept flowBuilding an agent in Copilot Studio
Building an agent in Copilot StudioBuilding an agent in Copilot StudioAgentname, instructions, personaTopics & triggersconversation flows & entry pointsActions & toolsconnectors, APIs, MCPKnowledgeground answers on your contentTest & publishchannels: Teams, web, more

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Sample AB-100 question

Case study — Contoso, Ltd. (custom AI agent). Contoso's custom AI agent must: draw on Dynamics 365 Supply Chain Management data to answer manufacturing-team questions as a low-code solution; be reachable from inside Microsoft Teams; be built so it can later hand off to other agents chosen by their descriptions; pick topics from a description of the query's intent rather than from a fixed trigger phrase, so conversations feel natural; and invoke Dynamics 365 Supply Chain Management business logic held outside the app. What should you configure for this custom AI agent?

  • Classic orchestration
  • Generative orchestration
  • Azure OpenAI reasoning models
  • AI-assisted evaluators
Explanation

Generative orchestration is correct. Rather than matching exact trigger phrases like classic orchestration, it uses natural language understanding to route to the right topic or connected sub-agent from a description of its purpose, delivering the low-code, conversational, interconnected experience required. Classic orchestration is trigger-phrase bound and scales poorly across linked agents; raw Azure OpenAI reasoning models are a pro-code, API-heavy route that breaks the low-code requirement; AI-assisted evaluators are testing/diagnostic tools, not a runtime orchestration engine.

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