Pattern Summary

Multi-Intent Fork is a parallel execution pattern where the agent detects or receives multiple distinct intents and pursues them concurrently. It’s designed to support users with overlapping goals, branching workflows, or simultaneous needs - without forcing a linear flow.

This pattern maximizes agent utility by breaking away from traditional step-by-step logic and enabling multiple lines of progress in parallel.

When to Use It

Use Multi-Intent Fork when:

  • The user expresses multiple goals in a single input or session
  • Tasks can be broken into parallelizable sub-tasks
  • The system needs to track and resolve multiple efforts independently
  • Context or session state supports concurrent threads of action

Examples include a meeting assistant scheduling multiple events, an agent drafting several documents based on topic cues, or a support bot handling different ticket types in one conversation.

How It Works

  1. Intent Recognition: Agent identifies two or more independent goals from user input or signals
  2. Parallel Branching: Agent launches or prepares discrete threads of action
  3. State Tracking: Each intent has its own context, progress, and resolution path
  4. Rejoining or Output: Agent may summarize results or bring threads back together as needed

Forks can be agent-managed in the background or surfaced to the user through UI elements.

Fit Assessment

Use this pattern if:

  • You want to avoid blocking behavior in multi-goal workflows
  • User goals are distinct but can run concurrently
  • The system can isolate and manage intent threads safely

Avoid using it when:

  • Intents are too tightly coupled to separate
  • Cognitive overload would result from showing too much parallel activity
  • System limitations prevent true parallelism (e.g., API, processing limits)

Acceptable Dependencies

✅ Strong intent recognition or classification
✅ Context isolation or containerized state per intent
✅ UI or logic support for switching, tracking, or summarizing multiple threads
✅ Optional: user controls to pause, prioritize, or close intents

Unacceptable Dependencies

❌ Collapsed or merged intent logic that ignores user distinctions
❌ Overlapping states that result in data leakage between threads
❌ No way for user or system to reconcile partial results

Implementation Starter Guide

  • Train models or prompts to detect and label separate intents
  • Maintain separate state objects per intent thread
  • Build UI affordances for switching between tasks or showing progress
  • Consider background vs foreground threading based on priority
  • Offer summary or resolution points that close each fork cleanly

Example: Product Setup Concierge

The user says: "Help me invite my team, set up notifications, and connect my calendar."

The agent responds:

"Got it - I’ll help with all three. Let’s start by inviting your team. I’ll also begin prepping your calendar sync in the background."

[Invite Team] [Notification Settings] [Calendar Sync]

Strategic Value

  • Mirrors real-world multitasking more effectively than linear flows
  • Increases perceived intelligence and helpfulness
  • Reduces user wait time or friction by working in parallel

Multi-Intent Fork enables agents to think like a power user - pursuing goals concurrently without dropping context.

Tags

Pattern Type: Parallelization, Intent Routing, Productivity
Scope: Multi-intent, Multi-session, Cross-context
Recommended UI Modes: Tabbed Panel, Expandable Cards, Notification Stack