How to Design a Multi‑Agent Collaborative Office Assistant System

Interview Scenario

Design a multi‑agent collaborative office assistant system.

Core Idea

The architecture relies on role division and a collaboration mechanism , with the Orchestrator Agent acting as the central hub.

Specialized Agent Team (Role Division)

Orchestrator Agent : Receives user requests, decomposes tasks, assigns them to appropriate agents, and aggregates results.

Schedule Agent : Manages calendars, arranges meetings, checks availability.

Email Agent : Handles sending and receiving emails, replies to common messages.

Document Agent : Creates, edits, organizes documents, performs knowledge‑base retrieval.

Data Agent : Queries data, generates reports, provides visual analysis.

Collaboration Mechanism

Task Allocation Process

User request → Orchestrator analyzes → Determines required specialized agents → Parallel dispatch for independent tasks → Collects each agent’s result → Produces final output.

Communication Methods

Message Queue : Asynchronous communication that decouples agents; suitable when tasks do not need immediate results.

Shared State Database : All agents read/write a common state store; suitable for scenarios requiring coordinated progress.

Event‑Driven : An agent publishes an event after completing a task, triggering downstream agents; suitable for pipeline‑style workflows.

Conflict Handling

Schedule Conflict : Resolved by the Schedule Agent, which offers multiple time options to the user.

Data Inconsistency : Avoided by using a single authoritative data source instead of separate copies.

Priority Rules : Configurable and transparent so users understand the execution order.

Ensuring State Consistency

The shared state database serves as a single source of truth. Write operations use locks or optimistic concurrency, and critical state changes emit events to notify relevant agents.

Real‑World Scenarios

Enterprise Office Assistant : User says “schedule tomorrow’s team meeting” → Orchestrator → Schedule Agent checks availability → Email Agent sends invitations → Document Agent prepares agenda.

Personal Productivity Assistant : User says “summarize this week’s work” → Orchestrator → Email Agent extracts important emails → Schedule Agent pulls meeting notes → Document Agent generates a weekly report.

Data Analysis Collaboration : User says “analyze last month’s sales data” → Orchestrator → Data Agent queries data → Document Agent creates a report → Email Agent distributes it to the team.

Key Takeaway

Multi‑agent office assistants consist of a dedicated agent team (role division) and a collaboration mechanism (task allocation, communication, conflict handling), with the Orchestrator Agent as the central hub.