Microsoft Agent Framework: Build and Orchestrate Multi-Agent AI Workflows in Python and .NET
Microsoft Agent Framework is an open-source library for building, coordinating, and deploying AI agents that can work together in complex pipelines — available for both Python and .NET developers. It supports graph-based workflows where multiple specialized agents hand off tasks to each other, with built-in features like checkpointing, human-in-the-loop approval steps, and a visual DevUI for debugging. Business owners can use it to automate multi-step processes like customer support escalation, document processing pipelines, or internal research workflows without stitching together separate tools.
MISSION OBJECTIVES
- 01Install the framework locally by running `pip install agent-framework --pre` in your terminal and verify it works by importing the package in a Python script.
- 02Clone the sample workflows directory from the GitHub repo (`python/samples/03-workflows/`) and run one of the pre-built multi-agent examples to see graph-based orchestration in action.
- 03Launch the DevUI package (`python/packages/devui/`) against your sample agent to visually inspect message flow, debug agent handoffs, and identify where to insert human-in-the-loop checkpoints.
CODE INTELLIGENCE
pip install agent-framework --pre
# .NET alternative:
# dotnet add package Microsoft.Agents.AIFIELD OPERATIONS
Customer Support Triage Pipeline
Build a multi-agent workflow where a routing agent classifies incoming support tickets by category and urgency, then dispatches to specialized agents (billing, technical, returns) that draft responses — with a human-approval checkpoint before any response is sent to the customer.
Automated Research Briefing System
Create a graph-based workflow with a search agent, a summarization agent, and a formatting agent that runs on a schedule, pulling news and competitor data, summarizing findings, and delivering a structured daily briefing document to a Slack channel or email.
STRATEGIC APPLICATIONS
- →A legal services firm uses a multi-agent pipeline where one agent extracts clauses from uploaded contracts, a second agent checks each clause against a compliance rulebook, and a third agent generates a risk summary report — cutting contract review time from hours to minutes.
- →An e-commerce company orchestrates post-purchase workflows where agents handle order confirmation, inventory updates, shipping notifications, and customer follow-up emails as a coordinated graph, replacing a fragile chain of Zapier automations with a single auditable, checkpointable pipeline.