Conversation Management

Manage multiple conversation sessions and organize your AI chat interactions effectively.

Overview

Conversation management in Agent M allows you to work with multiple conversation sessions simultaneously, keeping different projects and topics organized. You can:

  • Create new conversations for different projects or topics
  • Switch between conversations to work on multiple tasks
  • Organize conversations with descriptive names and tags
  • Manage conversation history to keep your workspace clean and efficient

Creating Conversations

Creating new conversations in Agent M is simple and intuitive. Start a fresh conversation by clicking the "New Conversation" button, which creates a new tab with a clean slate.

Conversation Types

Project Conversations

Perfect for ongoing projects where you need to maintain context over time

Exploration Conversations

Ideal for experimenting with new queries or data exploration

Documentation Conversations

Help you create and organize documentation

Learning Conversations

Great for trying out new MongoDB features or techniques

Naming Conversations

Giving your conversations descriptive names makes it much easier to find and organize your work:

  • Descriptive names: "User Management System" or "Sales Data Analysis"
  • Project-based naming: "Project Alpha - User Queries"
  • Date-based naming: "Daily Report - 2024-01-15"
  • Topic-based naming: "MongoDB Aggregation Examples"

Managing Multiple Conversations

Switching Between Conversations

Switching between conversations is designed to be quick and seamless:

Tab Navigation

Click on any conversation tab to switch instantly

Use tabs at the top of the interface

Keyboard Shortcuts

Navigate faster with shortcuts

Ctrl+Tab to cycle, Ctrl+1,2,3... to jump

Organizing Conversations

Conversation States

Active
Currently working
Paused
Set aside
Completed
Finished work
Archived
Saved reference

Conversation Context

Each conversation maintains its own context to keep your work organized:

Maintained Context

  • Previous queries in that session
  • Database context (which database you're querying)
  • AI conversation history
  • Saved queries from that session

Context Isolation

  • Separate query history for each conversation
  • Independent AI context for each conversation
  • Separate database connections if needed
  • Isolated settings for each conversation

Best Practices

Organization

  • Use descriptive names
  • Group related work
  • Regular cleanup
  • Consistent naming

Efficiency

  • Limit open conversations
  • Use keyboard shortcuts
  • Organize by project
  • Regular review

Collaboration

  • Share useful conversations
  • Document conversations
  • Use templates
  • Maintain consistency

Next Steps

Understanding Query Results

Learn how to interpret and work with query results in different formats, export data, and analyze results effectively.

Master query results →

Save Queries to Favorites

Organize frequently used queries, create personal libraries, and quickly access saved queries across conversations.

Build your library →