Agent Operative: Build Connected Agents

Key insights

• Multi-agent systems — The video shows how to upgrade a single agent into a coordinated multi‑agent system using connected and child agents.
  The walkthrough highlights adding an Application Intake Agent and an Interview Prep Agent to demonstrate real workflows.
• Child agents — Child agents run inside a parent agent’s workspace, share tools and knowledge, and do not require separate publishing.
  Use them for focused subtasks and fast iteration when you want tight integration and quick testing.
• Connected agents — Connected agents act as independent, full agents with their own topics, settings, and deployment lifecycle.
  Publish connected agents first so multiple teams or systems can reuse them across solutions.
• Copilot Studio patterns — Design agents with coordinator and worker roles to scale: one agent routes tasks while specialized agents execute in parallel.
  This modular approach improves reuse, reduces bottlenecks, and speeds end‑to‑end processing.
• Dataverse — Use Dataverse to persist context and pass structured data between agents, and design explicit return values so parent agents can continue processing reliably.
  Agents can also call other agents as tools to compose complex actions and keep conversation history where needed.
• Entra Agent ID — Follow governance and observability practices to track usage, cost, and performance, and to enforce secure agent identities.
  Well‑designed multi‑agent systems deliver faster automation, clearer ownership, and safer enterprise deployment.

Overview of the Video and Its Purpose

The video, published by Microsoft and presented by Scott Durow, explains how to upgrade a single agent into a coordinated multi‑agent system using Copilot Studio. It forms part of Agent Academy Mission 3, and it targets developers and makers who want practical guidance on agent orchestration. In addition, the clip outlines timestamps and step‑by‑step demos, making it easy to follow the learning path. Consequently, viewers can jump to topics like understanding multi‑agents, adding the Application Intake Agent, and attaching an Interview Prep connected agent.

Moreover, the video emphasizes two integration patterns: child agents, which run inside a parent workspace, and connected agents, which operate as separate, publishable units. Scott demonstrates how to design for scalability by composing smaller agents to handle focused tasks and by enabling them to communicate. He also shows the return-value patterns and the role of shared context for real enterprise workflows. As a result, the session balances conceptual design with hands-on examples to guide practical implementation.

What the Demonstration Shows

First, the demo walks through adding an Application Intake Agent that collects and preprocesses candidate data, then shows an Interview Prep Agent that builds targeted questions and summaries. Scott uses explicit instructions and structured return values so the main agent can direct collaborators and receive predictable outputs. Furthermore, the walkthrough highlights how agents can share context in the short term and use persistent storage for ongoing workflows. Therefore, the viewer sees how multi‑agent coordination moves from theory to applied tasks.

The presenter also points to practical features such as publishing lifecycles for connected agents and the automatic availability of child agents within a parent workspace. He explains where to use which pattern: child agents for quick, internal delegation and connected agents for autonomous, reusable services across teams. Additionally, the video includes timestamps that help teams reproduce the steps in Copilot Studio for their own scenarios. Consequently, developers gain a template for iterating on multi‑agent designs.

Architecture and Design Considerations

Architecturally, the video advises composing agents like a small team where each member has a clear responsibility, which reduces coupling and improves reuse. For example, one agent can handle intake, another validation, and a third can perform domain‑specific analysis, so parallel execution speeds up processing. At the same time, Scott highlights the need for defined communication patterns and return schemas so data flows reliably. Thus, designers must invest time in contract design to avoid brittle integrations.

Also, the demonstration discusses tooling and integration points such as using Dataverse for persistent context and governance interfaces to observe agent behavior. While these integrations increase enterprise readiness, they bring extra configuration and lifecycle management overhead for connected agents. Conversely, child agents simplify testing because they inherit the parent workspace but they do not scale independently. Therefore, teams must weigh convenience against maintainability when choosing patterns.

Tradeoffs and Operational Challenges

There are clear tradeoffs when balancing modularity, performance, and operational complexity in multi‑agent systems. On one hand, modular agents improve maintainability and allow specialized teams to own capabilities; on the other hand, they add network and orchestration complexity that requires monitoring and robust error handling. Moreover, publishing requirements for connected agents introduce release coordination, whereas child agents hide those lifecycle concerns but limit reuse outside the parent workspace. As a result, organizations face choices about deployment boundaries and team responsibilities.

Security and observability also present challenges, especially when agents act across systems or hold sensitive data. The video highlights governance needs and identity controls to ensure agents cannot bypass human review or access controls, and it suggests centralized monitoring to track costs and performance. Yet, implementing those safeguards increases engineering effort and may slow down innovation cycles. Consequently, teams must plan for ongoing operational costs and design clear escalation paths for failures.

Implications for Developers and Enterprises

For developers, the video provides a practical roadmap to adopt multi‑agent coordination: start small with child agents to validate ideas, then evolve to connected agents for cross‑team reuse. It encourages clear instruction patterns and structured outputs to make collaboration predictable and testable, which accelerates development while reducing surprises during integration. Additionally, learning the publishing and lifecycle mechanics prepares teams for production readiness. Therefore, the tutorial serves both as a training piece and an architectural reference.

For enterprises, the guidance points to measurable benefits such as faster processing, reduced manual toil, and the opportunity to automate multi‑step workflows at scale. Nevertheless, these gains come with operational costs in governance, identity management, and observability, and they require cultural changes for teams to coordinate ownership. Ultimately, the video by Microsoft delivers actionable steps and realistic tradeoffs so organizations can make informed decisions while adopting multi‑agent systems in real world settings.

Keywords

multi-agent AI, connected agents tutorial, agent orchestration, multi-agent system integration, AI agent collaboration, make agent multi-agent ready, Agent Operative Mission 3, build connected agent network