Develop AI agents with Microsoft Foundry and Visual Studio Code | AI-103 | Episode 7

AI agents add an orchestration layer above an LLM: model + instructions + tools + conversation state work together in an agentic loop to complete multi-step tasks rather than simply return a response.

Core Architecture

Application → Foundry Project → Agent → Model + Instructions + Tools

Microsoft Foundry Agent Service provides a managed runtime for conversation state, tool calling, and agent lifecycle. Agents can invoke built-in tools such as File Search for grounded retrieval and Code Interpreter for Python-based analysis, plus APIs and custom functions.

Build & Integrate

Typical flow:

Create project → Deploy model → Define agent → Configure instructions/tools → Test → Consume from application

The Foundry portal is useful for prototyping; SDK/code-based configuration improves repeatability, version control, and CI/CD.

from azure.ai.projects import AIProjectClient
from azure.identity import DefaultAzureCredential

project = AIProjectClient(
    endpoint=PROJECT_ENDPOINT,
    credential=DefaultAzureCredential()
)

openai = project.get_openai_client()

Key Distinctions to Remember

Project endpoint ≠ model endpoint. When working through Foundry, AIProjectClient connects to the Foundry project endpoint. The project client can provide an OpenAI-compatible client for Responses, Conversations, and related operations.

Conversation state can be server-side. Conversations are durable objects containing messages, tool calls, and tool outputs, allowing the same conversation to continue across requests.

Tools determine agent capabilities. File Search provides grounding/RAG; Code Interpreter executes analysis; custom functions/APIs allow agents to take actions.

Managed Agent Service vs. direct model API: the managed runtime handles infrastructure such as conversation management, tool execution/orchestration, and agent lifecycle, while application code operates at a higher abstraction.

Exam mental model: know what belongs to the project, agent, model, conversation, and tool layers—and which SDK/client or endpoint your application is actually targeting.