Chat Usage

Introduction to Chat Functionality

ELITEA Chat is a powerful feature designed to centralize your interactions with various ELITEA components, enabling you to achieve optimal results efficiently.

A Conversation in ELITEA represents a dynamic dialogue involving multiple participants. These can include language models (LLMs), Agents, Pipelines, Toolkits, MCPs, and human Users like yourself. You interact using natural language, and the chat maintains context, allowing you to refer to previous messages within the same conversation. Conversations are isolated; context is not shared between different conversations.

All your conversations are securely stored on the ELITEA server, making them accessible from any device where you log in. You can find all your conversations listed under the Chat menu in the sidebar.

Key Features

• Public and Private Conversations: Control visibility and collaboration by sharing conversations or keeping them private.
• Diverse Participants: Integrate Models, Agents, Pipelines, Toolkits, MCPs, and other Users (in public conversations) into your chat.
• Canvas Editor: Edit and refine AI-generated code, tables, and diagrams with built-in editing tools.
• File Attachments: Upload and attach images and files for AI analysis and processing.
• Internal Tools: Execute Python code securely with the Python Sandbox internal tool.
• Rich Interactions: Engage with participants, copy responses, provide feedback, and more.
• Comprehensive Management: Save, pin, share, delete, and clear conversations.
• Folder Organization: Structure your conversations logically using folders.
• Playback Mode: Simulate and review conversation flows without engaging live models, ideal for demos.
  ## Getting Started

Creating a New Conversation

1. In the main sidebar on the left, locate the Chat section.
2. Click + Create to start a new conversation.
3. The chat input field appears and is highlighted to focus your attention.
4. You'll see a welcome screen with the message "Hello, [Your Name]! What can I do for you today?"
5. The message input box at the bottom shows the placeholder: "Type your message. Use # to search and add AI assistants to conversation."
6. Choose your approach:
   • Add a participant first: Type # to search and select an Agent, Pipeline, Toolkit, or MCP from the dropdown list that appears. Selected participants will appear as chips above the input box.
   • Select a model: Click the model selector dropdown to choose an LLM (e.g., GPT-4, Claude).
7. Type your message: Enter your initial message, question, or command (e.g., "Help me write a Python script", "What are the best practices for API design?", "Explain quantum computing").
8. Send: Click the Send icon (paper airplane icon) or press Enter.
9. The new conversation is created and appears in the CONVERSATIONS sidebar on the left.
10. The conversation name is automatically generated based on your message content. During name generation (1-2 seconds), you'll see a loader icon with "Naming" text next to the conversation item. You can manually rename it at any time after generation completes.

Creating a New Folder

Organize your conversations by grouping them into folders.

1. In the Conversations sidebar, locate the folder icon button next to "Conversations" at the top.
2. Click the folder icon (Create folder button).
3. A new folder entry will appear. Enter a descriptive Name for your folder.
4. Press Enter or click the checkmark to save.

The new folder will appear in your CONVERSATIONS sidebar.

Managing Conversations

Moving Conversations to Folders

To organize conversations into folders:

Method 1: Drag and Drop

1. In the CONVERSATIONS sidebar, click and hold on the conversation you wish to move.
2. Drag the conversation over the destination folder.
3. Release to drop the conversation into the folder.

Method 2: Context Menu

1. In the CONVERSATIONS sidebar, right-click on the conversation you wish to move.
2. Select Move to from the context menu.
3. Choose the desired destination folder from the list, OR
4. Select Create folder to create a new folder and move the conversation into it simultaneously.
5. To move a conversation back to the main list, select Back to the list from the Move to menu.

Conversation Actions (Sidebar)

You can manage conversations directly from the CONVERSATIONS sidebar by right-clicking on a conversation or clicking the options menu (often ...) associated with it. The following actions are available:

• Edit: Rename the conversation. Enter the new name and confirm.
• Pin / Unpin: Select Pin to keep the conversation at the top of the list for easy access. Select Unpin on a pinned conversation to remove it from the top.
• Move To: Move the conversation into a folder, as described above.
• Make Public: Convert a private conversation into a public one, visible to other project members.
  Caution: This action is irreversible; you cannot make a public conversation private again.
• Share: To share a conversation with team members, select Share from the conversation contextual menu. This action copies a direct link to the conversation to your clipboard. Team members can use this link to access and view the conversation. (available for team project)
• Delete: Permanently remove the conversation. You will be asked to confirm this action.
• Playback: Enter Playback mode for this conversation (See Playback Mode).

Sharing Conversations

The conversation sharing feature allows you to share conversations with team members by providing them with a direct link. This is particularly useful for collaboration, code reviews, troubleshooting, and knowledge sharing within your team.

Important Permissions

• Team Projects Only: Conversation sharing is only available for conversations in team projects. You cannot share conversations from personal projects.
• Team Members: Only team members who have access to the project can view shared conversations.
• Access Level: Recipients must have appropriate permissions within the project to access the shared content.

How Conversation Sharing Works

When you share a conversation, ELITEA generates a unique URL that includes the conversation ID, name, and a special parameter that identifies it as a shared conversation. Team members who receive this link can access and view the complete conversation history in their browser.

How to Share a Conversation

1. Navigate to the CONVERSATIONS sidebar in the Chat section.
2. Locate the conversation you want to share.
3. Hover over the conversation to reveal the contextual menu.
4. Select Share from the menu options.
5. The conversation link is automatically copied to your clipboard.
6. You will see a notification: "The link has been copied to the clipboard."
7. Paste the link in your communication channel (email, Slack, Teams, etc.) to share it with team members.

Use Cases for Sharing Conversations

• Collaboration: Share conversations to involve team members in ongoing discussions or problem-solving sessions
• Code Reviews: Share conversations containing code generation or refactoring for peer review
• Troubleshooting: Share error discussions with technical support or senior team members
• Knowledge Transfer: Share valuable conversations as learning resources for team members
• Documentation: Share conversations that demonstrate best practices or solutions to common problems
• Demos and Presentations: Share conversations to demonstrate ELITEA capabilities or AI-assisted workflows

Sharing vs Making Public

The Share action is different from Make Public. Sharing creates a link for easy access while maintaining existing permissions, whereas making a conversation public changes its visibility settings permanently and cannot be reversed.

Accessing Shared Conversations

When a team member clicks on a shared conversation link:

1. The link opens in their browser
2. ELITEA automatically navigates to the specified conversation
3. The conversation opens with the complete history visible
4. The recipient can read the entire conversation thread
5. Depending on their permissions, they may be able to interact with or continue the conversation

Access Permissions

If a user doesn't have access or permissions to the shared conversation (i.e., the conversation is not public and the user is not added as a participant), clicking the shared link will navigate them to the chat interface, but they will not be able to view the conversation content. This is the expected behavior to maintain conversation privacy and security.

Managing Folders

Folder Actions (Sidebar)

Folders can be managed directly from the CONVERSATIONS sidebar. Right-click on a folder or click its associated options menu (...) to access the following actions:

• Edit Folder: Rename the folder. Enter the new name and click the checkmark (✔) or Save button.
• Delete Folder: Remove the folder.
  Important: Deleting a folder does not delete the conversations inside it. Conversations within a deleted folder are automatically moved back to the main conversation list (root level). You will be asked to confirm deletion.

Understanding Conversation/Folder Visibility

Access and permissions depend on the project type (Private vs. Team) and the conversation/folder setting (Private vs. Public).

Private Conversations and Folders

• Created within your private workspace or designated as private within a team project.
• Only visible and accessible to you, the creator.
• You can add Agents, Pipelines, MCPs and Toolkits as AI Assistants.
• You cannot add other Users as participants to private conversations.

Team Project Conversations and Folders

When working within a shared team project:

• Folders: You can see all folders created within the project.
• Conversations: You can only see conversations within folders if you are a member (participant) of that specific conversation.
• Membership Actions: If you are a member of a conversation, you can move it into any folder (public or private if you created it) or move it out of a folder using the Back to the list option (often found within the Move To menu).
• Folder Restrictions: You generally cannot delete folders created by other users, even if you can manage conversations within them.

Example: Collaboration in a Team Project Chat

Scenario:
The QA, PM, and BA are working together on a new feature for a product. They are using a shared conversation to discuss requirements, testing strategies, and project timelines.

Steps to Collaborate:

• BA Adds Requirements:
  The BA starts the conversation by adding the feature requirements.
  Example:
  

  @BA: "The new feature should allow users to upload files up to 10MB in size. The system must validate file types and provide error messages for unsupported formats."
  

• PM Sets the Timeline:
  The PM responds by setting the timeline for the feature's development and testing.
  Example:
  

  @PM: "The development team will complete the implementation by May 15th. QA can start testing on May 16th, and we aim to release the feature by May 20th."
  

• QA Plans Testing:
  The QA outlines the testing strategy and asks for clarification on edge cases.
  Example:
  

  @QA: "I will create test cases for file uploads, including valid and invalid file types, file size limits, and error handling. @BA, can you confirm if the system should support drag-and-drop uploads?"
  

• BA Provides Clarifications:
  The BA clarifies the requirements and provides additional details.
  Example:
  

  @BA: "Yes, drag-and-drop uploads should be supported. Additionally, the system should display a progress bar during uploads."
  

• PM Tracks Progress:
  The PM uses the chat to track progress and ensure alignment.
  Example:
  

  @PM: "QA, please share the test results by May 18th so we can review them before the release."
  

Using Folders for Organization

• The PM creates a folder named "Feature: File Upload" to organize all conversations related to this feature.
• The conversation is moved into this folder for easy access by all team members.

Collaboration Benefits

• Centralized Communication: All discussions, clarifications, and updates are stored in one place.
• Transparency: Team members can see the progress and contribute as needed.
• Accountability: Each participant's responsibilities and deadlines are clearly outlined.

Tips for Effective Collaboration in Team Projects

• Use Mentions: Use @ to mention specific teammates.
• Organize Conversations: Use folders to group related conversations for better accessibility.
• Set Clear Expectations: Define roles, responsibilities, and deadlines within the chat.
• Provide Updates: Regularly update the chat with progress, blockers, and next steps.

Public Conversations and Folders

• Folders: Public folders are visible to all members of the project.
• Conversations: Conversations within public folders (or marked as public) can be viewed and interacted with by all project members. Any member interacting becomes a participant.
• Permissions: Project members can typically move conversations into or out of public folders, subject to their overall project permissions.
• Irreversibility: Public folders/conversations cannot be converted back to private.

Working with Participants

Participants are the core components you interact with within a conversation.

What are Participants?

Participants are the "tools" or "entities" you add to your chat. These include:

• Models: Large Language Models (e.g., GPT-4, Claude) for generating text, answering questions, etc.
• Agents: Pre-configured automated workflows or specialized bots designed for specific tasks.
• Pipelines: Multi-step automated processes that orchestrate multiple agents and tools.
• Toolkits: Collections of tools and integrations that extend chat capabilities (e.g., GitHub, Jira, Confluence).
• MCPs: Model Context Protocol servers that provide external tool capabilities (e.g., Playwright for browser automation, Figma for design files).
• Users: In public conversations, other project members who join or interact become participants. They cannot be manually "added" like other types but join implicitly.

Adding Participants to a Conversation

To add participants:

Method 1: Using the Participants Panel

1. In the Participants section on the right side of the screen, you'll see collapsible sections for:
2. Users (if in a team project)
3. agents
4. pipelines
5. toolkits
6. MCPs
7. Click the + icon next to any section title to add participants of that type.
8. Once participants are added, type your message and click Send.

Method 2: Using the # Symbol (Frequently Used)

1. In the chat input box, type # to see a dropdown list of frequently used participants.
2. Continue typing to filter participants by name (e.g., #Jira will show all Jira-related participants).
3. Select a participant from the filtered list (e.g., #Data Analysis Agent, #Jira Toolkit).
4. The selected participant will appear as a chip above the input box and in the
5. Type your message and click Send.

Creating New Participants from Chat:

You can also create new participants directly from the chat interface using the Canvas feature:

• Agents: Click Create new agent to open the Agent Canvas and configure a new AI agent. See How to Create and Edit Agents from Canvas.
• Pipelines: Click Create new pipeline to open the Pipeline Canvas and design a multi-step workflow. See How to Create and Edit Pipelines from Canvas.
• Toolkits: Click +Add toolkit then + Create new Toolkit to configure integrations like GitHub, Jira, etc. See How to Create and Edit Toolkits from Canvas.
• MCPs: Click Create new MCP to connect Model Context Protocol servers. See How to Create and Edit MCPs from Canvas.

Adding Users to a Conversation

Users (team members) can only be added to in team projects. They cannot be added to private conversations.

To Add Users:

1. Ensure your conversation is in team Project.
2. In the Participants section on the right side, locate the Users section.
3. Click the + icon next to Users.
4. A list of available team members will appear.
5. Select the user(s) you want to add to the conversation.
6. The selected users will appear in the Users section of the Participants panel.

Important Notes:

• Added users will receive notifications about being added to the conversation.
• Users can also join a public conversation implicitly by interacting with it.
• Once a conversation is public, it cannot be converted back to private.

For detailed information on adding teammates, see Adding Teammates to Conversation.

Using Participants in a Conversation

Once added, participants are ready to process your messages:

1. Check Participants: Ensure the desired participant is listed in the Participants section.
2. Select Active Participant(s):
   • Click: Click the participant's name/icon in the Participants list to make it active for your next message.
3. Mention Users (Team Projects only): You can mention other team members using @ followed by their name (e.g., @John Doe). This notifies them and brings their attention to specific parts of the conversation.
4. Send Message/Command: Type your message or a simple command (like "Go", "Execute", "Run it") and press Send. The active participant(s) will process your input.

Example Usage

• To ask a general question using a specific model:

  1. Select a model from the model selector dropdown (e.g., GPT-4o).
  2. Type: "Explain the concept of recursion in programming." -> Send.

• To use a specific agent:

  1. In the Participants panel, click the + icon next to "agents".
  2. Select Data Analysis Agent from the dropdown.
  3. Click on the agent in the Participants list to activate it, or type #Data Analysis Agent in the input box.
  4. Type your request: "Analyze the latest sales data." -> Send.

• To use a toolkit:

  1. Add the desired toolkit (e.g., Artifact Toolkit) from the toolkits section.
  2. Type: "Store this data in artifacts." -> Send.

• To mention a team member (Team Projects only):

  1. In your message, type @ followed by the team member's name (e.g., @John Doe).
  2. Type: "@John Doe, can you review this analysis?" -> Send.

Selecting and Configuring Models

Models are the large language models (LLMs) that power your conversations. You can select a model and adjust its behavior to suit your needs.

Selecting a Model:

1. In the conversation interface, locate the model selector dropdown at the top of the chat area.
2. Click the dropdown to see the list of available models (e.g., GPT-4o, Claude, GPT-3.5).
3. Select the desired model from the list.
4. The selected model will be used for your next message and subsequent messages until you change it.

Configuring Model Settings:

Click the Settings (⚙️) icon next to the model selector to fine-tune the response generation. The settings vary depending on the selected model:

For Reasoning Models (e.g., GPT-5.1):

• Reasoning - Controls the depth of logical thinking and problem-solving with three levels:
  • Low: Fast, surface-level reasoning with concise answers and minimal steps
  • Medium: Balanced reasoning with clear explanations and moderate multi-step thinking (default)
  • High: Deep, thorough reasoning with detailed step-by-step analysis (may be slower)

For Standard Models (e.g., GPT-4o):

• Creativity - Controls response randomness and creativity. Lower values produce more focused and deterministic outputs, while higher values generate more diverse and creative responses with five levels (1-5):
  • 1: Highly focused and deterministic outputs
  • 2: Mostly focused with slight variation
  • 3: Balanced between focus and creativity (default)
  • 4: More varied and creative responses
  • 5: Maximum creativity and diversity

Max Completion Tokens (All Models):

Limits the maximum length of AI responses measured in tokens (roughly 4 characters per token):

• Auto (default): System automatically sets the token limit to 4096 tokens
• Custom: Manually set a specific token limit for responses
  • When Custom is selected, you can enter a specific number of maximum tokens
  • The interface shows remaining tokens available after your specified limit
  • Setting too high a value will show an error if it exceeds the model's maximum output tokens

Configuring Participants

You can configure and edit participants (Agents, Pipelines, Toolkits, and MCPs) directly within the conversation using the Canvas editor.

Accessing Participant Settings:

1. Option 1: Click the participant in the Participants list, then click the ⚙️ (settings) icon.
2. Option 2: Hover over the participant element in the Participants list and click the Edit icon that appears.
3. The appropriate Canvas editor will open based on the participant type.

What You Can Configure:

• Agents:

  • Edit the agent's prompt and instructions
  • Modify variables used by the agent
  • Configure model settings (Temperature, Top P, Top K, Maximum Length)
  • Select the agent version (default is "latest")
  • Adjust toolkits and integrations

• Pipelines:

  • Edit the pipeline workflow and step sequences
  • Modify variables and parameters
  • Configure agents used in the pipeline
  • Adjust toolkits and integrations
  • Select the pipeline version (default is "latest")

• Toolkits:

  • Configure integration settings and credentials
  • Adjust tool parameters and options
  • Enable or disable specific tools within the toolkit
  • Modify connection settings for external services

• MCPs (Model Context Protocol servers):

  • Configure server connection settings
  • Adjust tool availability and permissions
  • Modify environment variables and parameters
  • Set timeout and performance options

Note

MCP servers must be running before they can be used in conversations. Ensure your MCP server is started and accessible before adding it as a participant.

Applying Changes:

1. Make your edits in the Canvas editor.
2. Click the Save button to apply your modifications.
3. The updated configuration will be used for subsequent messages in the conversation.

Displaying Configured Conversation Starters

When you add a participant (like an Agent, Pipeline, Toolkit, or MCP) that has a pre-configured "conversation starter" message or instruction set, this message will automatically appear in the chat. This helps guide you on how to interact with the participant effectively.

Interacting with Conversation Outputs

Like/Dislike and Commenting

1. Below each generated response, you'll see Thumbs Up (👍) and Thumbs Down (👎) icons.
2. Click Thumbs Up to indicate satisfaction.
3. Click Thumbs Down to indicate dissatisfaction.
4. After clicking Thumbs Down, a Leave comment field appears. Click it, type your specific feedback or reason for disliking, and press Send (or Enter). This feedback is valuable for improving models and prompts.

Regenerating the Last Output

1. If you're not satisfied with the very last response generated by a participant, you can ask it to try again.
2. Ensure a response has been generated.
3. Click the Regenerate icon 🔄 usually located near the last message or the input box.
4. The system will use the same input/prompt that generated the last response and attempt to create a new, potentially improved, output.

Using Canvas for Content Editing

Canvas is your all-in-one workspace for editing, refining, and collaborating on AI-generated content in ELITEA. Instead of copying results into other tools, you can work directly with code, tables, and diagrams—right where the conversation happens.

What is Canvas?

Canvas is a built-in editor that appears automatically when ELITEA generates code, tables, or Mermaid diagrams in a chat. It allows you to edit, refine, and export AI-generated content without leaving the conversation.

Canvas Features:

• Code Editor: Edit code with syntax highlighting, find/replace, and code folding. Export as various file formats (e.g., .py, .js, .java).
• Table Editor: Modify tables with spreadsheet-like functionality. Add/remove rows and columns, sort, filter, and export to XLSX or Markdown.
• Diagram Editor: Edit Mermaid diagrams with live preview and syntax highlighting. Export as PNG, JPG, or SVG.

How to Use Canvas:

1. Ask ELITEA to generate code, a table, or a Mermaid diagram.
2. When ELITEA generates the content, look for the pencil icon (✏️) in the top-right corner of the content block.
3. Click the icon to open the Canvas editor in a modal window.
4. Make your edits using the available tools:
   • Copy: Copy content to clipboard
   • Undo/Redo: Revert or reapply actions
   • Save: Save your changes
   • Export: Download in various formats
5. Click Save to preserve your changes in the conversation or Export to download files.

For detailed information, real-world examples, and best practices, see Canvas in Conversation.

Attaching Files and Images

ELITEA Chat supports attaching files and images to your conversations, enabling AI-powered analysis of visual content and documents.

How It Works:

The attachment functionality is integrated with the Artifact Toolkit. When you enable attachments for an Agent, Pipeline, or a specific chat, files are automatically uploaded and stored in the Artifact bucket associated with that toolkit. Files are subject to the retention policy of the bucket (default: 30 days).

Key Features:

• Multiple Upload Methods: Click the paperclip icon, drag and drop files, or paste from clipboard (Ctrl+V or Cmd+V).
• Supported Formats: JPEG, JPG, PNG, GIF (first frame only), WebP images.
• File Limits: Maximum 10 images per message. Size limits depend on the AI model (e.g., Anthropic: 5MB, OpenAI: 20MB per image).
• Artifact Integration: Files are stored in Artifact buckets with configurable retention policies.
• Management Options: Download or delete attachments directly from chat.

To Enable Attachments:

From Chat:

1. Click the paperclip icon in the message input area.
2. If not configured, the Attachment settings popup will appear.
3. Select an existing Artifact Toolkit or create a new one.
4. Once configured, you can attach files by clicking the paperclip, dragging files, or pasting.

Using Attachments:

1. After enabling, click the paperclip icon to see "Attach files" and "Attachment settings" options.
2. Attach images using click, drag-and-drop, or paste methods.
3. Type a text prompt to accompany your images (required).
4. Click Send to submit the message with attachments.

For complete setup instructions, advanced configuration, and troubleshooting, see Attachments in Conversation.

Using Internal Tools

Internal tools provide built-in capabilities that enhance your conversations without requiring external integrations. These tools can be enabled directly from the chat interface or configured as part of an agent's default setup.

Available Internal Tools

Python Sandbox

Execute Python code securely in conversations using Pyodide (Python compiled to WebAssembly). Useful for calculations, data processing, testing algorithms, and generating visualizations.

• Secure Code Execution: Run Python code in a secure sandbox environment
• Package Support: Install and use Python packages like numpy, pandas, and matplotlib
• Persistent State: Code execution maintains state within the same conversation
• Visualizations: Generate data visualizations and reports
• Use Cases: Execute code snippets, perform calculations and data analysis, test algorithms, and process data

Planner

Create, manage, and track tasks and action items directly within conversations. Set priorities, due dates, and monitor task progress without switching to external task management tools.

• Task Decomposition: Break down complex requests into smaller, actionable tasks
• Workflow Organization: Create structured plans with clear steps and dependencies
• Progress Tracking: Monitor task completion and workflow progress with priority levels (High/Medium/Low)
• Task Status: Track tasks through Pending, In Progress, and Completed states
• Use Cases: Project planning, feature development breakdown, complex problem-solving, and workflow design

Data Analysis

Perform Pandas-based data analysis on uploaded files (CSV, Excel, etc.) using natural language queries. Automatically processes data and generates charts with downloadable results.

• Natural Language Processing: Use plain English to request data analysis operations
• File-Based Analysis: Works with files uploaded directly to conversations
• Automated Processing: Intelligent file format detection and data analysis
• Chart Generation: Automatic creation of visualizations with downloadable results
• Use Cases: Data exploration, statistical analysis, trend identification, and report generation

Enabling Internal Tools in Conversations

1. Navigate to your conversation
2. Locate the Internal Tools icon (value icon) in the chat input toolbar at the bottom of the screen, next to the attachment button
3. Click the Internal Tools icon to open the configuration popup
4. Find the tool you want to enable in the list
5. Click the toggle switch next to the tool name to enable it
6. A success notification will appear: "Internal tools configuration updated"
7. Click anywhere outside the popup to close it

Once enabled, the AI assistant can automatically use these tools during conversations when appropriate.

Enabling Internal Tools in Agents

You can also enable internal tools as part of an agent's default configuration in the TOOLKITS section. This makes the tools available in all new conversations using that agent.

1. Navigate to Agents in the main menu and select the agent
2. Click the Configuration tab
3. Scroll to the TOOLKITS section
4. Find the internal tool switches (Python sandbox, Planner, Data Analysis) and toggle them ON as needed
5. Click Save at the top of the configuration page
6. The enabled internal tools will be available in all new conversations using this agent

Using Internal Tools

Once enabled, the AI assistant can use the internal tools during conversations:

• Python Sandbox: The assistant can execute Python code, install packages, perform calculations, and generate visualizations
• Planner: The assistant can break down complex tasks, create structured plans with priorities and due dates, and track task progress
• Data Analysis: The assistant can perform comprehensive data analysis on uploaded files using natural language commands

For detailed usage examples, troubleshooting, and best practices, see:

• Python Sandbox Guide
• Planner Internal Tool Guide
• Data Analysis Internal Tool Guide

Playback Mode

Playback mode allows you to step through an existing conversation turn by turn, exactly as it happened, without actually sending requests to the Models, Toolkits, etc.

• Purpose: Excellent for demonstrating a workflow, reviewing a complex interaction, or debugging without incurring processing costs or waiting for live responses.
• Activation: Access this via the conversation's context menu in the sidebar (Right-click conversation -> Playback).
• Controls: During playback, you typically have controls to move forward to the next message, go back to the previous message, or stop the playback simulation.

Example: Using Playback Mode for a Demo

Scenario:
A Product Manager is preparing a demo for stakeholders to showcase how the team collaborated on a new feature. They use Playback Mode to simulate the conversation and highlight key decisions and actions.

Steps to Use Playback Mode:

Access the Conversation:
The Product Manager navigates to the conversation in the CONVERSATIONS sidebar where the team discussed the feature.

Activate Playback Mode:
The Product Manager right-clicks on the conversation and selects Playback from the context menu.

Simulate the Conversation:
- The playback starts with the BA's initial message outlining the feature requirements.
Example:

@BA: "The new feature should allow users to upload files up to 10MB in size. The system must validate file types and provide error messages for unsupported formats."

- The PM uses the Next control to move to the next message, where they set the timeline for development and testing.
Example:

@PM: "The development team will complete the implementation by May 15th. QA can start testing on May 16th, and we aim to release the feature by May 20th."

- The QA's message about testing strategies is reviewed next.
Example:

@QA: "I will create test cases for file uploads, including valid and invalid file types, file size limits, and error handling."

Highlight Key Decisions:
- The Product Manager pauses playback to explain the rationale behind certain decisions, such as the timeline or testing strategy. - They resume playback to show the BA's clarification about drag-and-drop uploads.
Example:

@BA: "Yes, drag-and-drop uploads should be supported. Additionally, the system should display a progress bar during uploads."

Conclude the Demo:
- The Product Manager stops playback after showcasing the final message tracking progress.
Example:

@PM: "QA, please share the test results by May 18th so we can review them before the release."

Benefits of Playback Mode for Demos

• Polished Presentations: Playback Mode ensures a smooth and professional demo without interruptions or delays.
• Clarity: Stakeholders can see the exact flow of discussions and decisions.
• Engagement: The step-by-step simulation keeps the audience engaged and focused on key points.

By using Playback Mode, teams can effectively demonstrate their collaboration and decision-making processes to stakeholders, ensuring transparency and alignment.