AI-901 - Implement AI solutions by using Microsoft Foundry - Section 2.1

Implement generative AI apps and agents by using Foundry, including prompts, deploying and interacting with a model, the Foundry SDK, and single-agent solutions.

Writing effective system and user prompts for generative models; deploying a model and interacting with it in the Foundry portal; building a lightweight chat client with the Foundry SDK; and creating and testing a single-agent solution in the Foundry portal. The reliable single-best distractions are choosing the portal where the SDK is required (or the reverse), and collapsing an agent (which plans and calls tools or knowledge to complete a task) into a plain generative chat completion.

system and user promptsMicrosoft Foundry portalFoundry SDKdeploy a model in Foundrysingle-agent solutionagent client application

Practice question for this objective

Free sampleImplement AI solutions by using Microsoft Foundryhard

A developer is deciding between building a single-agent solution and simply calling a deployed model with a plain chat completion request. Which statement correctly describes when the single-agent solution is warranted?

  • AA single agent is warranted when the task requires planning steps and calling tools or knowledge to act, whereas a plain chat completion only returns a generated reply. Correct
  • BA single agent is warranted whenever the reply needs to be longer than a plain chat completion is able to return in one response.
  • CA plain chat completion is warranted whenever the answer must be in British English, because an agent cannot be told which language to use.
  • DThe two are interchangeable, and the only real difference is which button is selected in the Foundry portal when the model is deployed.
Distinguish a single-agent solution, which plans and calls tools to act, from a plain chat completion that only returns a reply. A plain chat completion returns generated text from the model, but a single-agent solution can plan a sequence of steps and invoke tools or knowledge to carry out actions towards a goal, which is the capability that justifies building an agent.

Why A is correct: Correct: an agent adds planning and the ability to call tools or knowledge sources to complete a goal, while a plain chat completion just generates a reply from the model.

Why B is wrong: Response length is not what separates the two; both approaches ultimately produce model output, so length alone is not a reason to build an agent.

Why C is wrong: This is a distraction: language and tone are set through instructions in either approach, so an agent is perfectly able to reply in British English.

Why D is wrong: It is tempting to treat them as the same feature with different labels, but they differ in capability: an agent can plan and act, which a plain completion cannot.

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