AI Project Manager Chat Assistant

What This Agent Does

The Project Manager Agent is an intelligent automation workflow designed to streamline task creation and project management directly through chat. This agent intelligently gathers project information through conversational interaction, validates that all necessary details are collected, and automatically logs tasks to your Google Sheet for centralized tracking and team collaboration.

By automating the task intake process, this agent eliminates manual data entry, reduces context-switching, and ensures consistent task documentation. Teams can now create and track project tasks in seconds rather than minutes, while maintaining a single source of truth in Google Sheets. Whether you're managing sprint planning, bug tracking, or general task assignment, this agent adapts to your workflow and saves your team valuable time every day.

Key Benefits:

• Intelligent Information Gathering: Conversational AI asks only the questions needed to complete your task
• Automatic Validation: Ensures all critical information is captured before logging tasks
• Seamless Integration: Directly populates your Google Sheet with properly formatted task data
• Reduced Manual Work: Eliminates copy-pasting and manual spreadsheet updates
• Consistent Documentation: Every task follows the same structure and quality standards

Target Use Cases:

• Agile sprint planning and backlog management
• Bug and issue tracking workflows
• Feature request intake and prioritization
• Team task assignment and delegation
• Project milestone tracking and documentation

Who Is It For

This workflow is ideal for project managers, team leads, and operations professionals who need to quickly capture and organize tasks without leaving their chat interface. It's particularly valuable for:

• Distributed teams that rely on asynchronous communication
• Fast-paced environments where speed of task creation matters
• Organizations using Google Workspace for collaboration and data storage
• Teams managing multiple projects that need centralized task tracking
• Anyone tired of context-switching between chat, email, and spreadsheets

No technical expertise is required to use this agent—just natural conversation!

Required Integrations

Chat Integration

Why It's Needed: The Chat integration serves as the user-facing interface for your Project Manager Agent. It enables team members to trigger the workflow, interact with the AI agent conversationally, and receive real-time feedback about task creation status.

Setup Steps:

1. Navigate to Integrations in your TaskAGI dashboard
2. Search for and select Chat from the available integrations
3. Click Connect or Enable
4. Authorize TaskAGI to access your chat platform (Slack, Teams, Discord, or custom chat)
5. Select the specific channel or workspace where the agent should operate
6. Configure notification preferences for task confirmations
7. Save and verify the connection shows as Active

How to Obtain Credentials:

• For Slack: Generate a bot token from your Slack App settings (requires workspace admin access)
• For Microsoft Teams: Create an app registration in Azure AD
• For Discord: Create a bot application and obtain the bot token
• For Custom Chat: Use your platform's API documentation to generate authentication tokens

Configuration in TaskAGI:

• Set the Chat Trigger node to listen for specific keywords like "create task" or "new project"
• Configure response formatting to match your team's communication style
• Enable message threading to keep task conversations organized
• Set up notification channels for task completion confirmations

Google Sheets Integration

Why It's Needed: Google Sheets serves as your persistent task database, creating a centralized record of all tasks created through the agent. This integration automatically appends task information collected by the AI agent directly into your spreadsheet, eliminating manual data transfer and keeping your project management system up-to-date in real-time.

Setup Steps:

1. Open your Google Sheets account and create a new spreadsheet (or use an existing one)
2. Set up column headers in the first row:
   • Task Name | Description | Assigned To | Priority | Due Date | Status | Created Date
3. Navigate to Integrations in TaskAGI and search for Google Sheets
4. Click Connect and authorize TaskAGI to access your Google account
5. Grant permissions for read and write access to Google Sheets
6. Return to TaskAGI and select your spreadsheet from the dropdown
7. Select the specific sheet tab where tasks should be appended
8. Test the connection by clicking Verify Integration

How to Obtain API Keys/Credentials:

• Google Sheets uses OAuth 2.0 authentication (no manual API key needed)
• When you click Connect, you'll be redirected to Google's login
• Sign in with the Google account that owns your spreadsheet
• Grant TaskAGI the requested permissions
• You'll be automatically redirected back to TaskAGI with credentials stored securely

Configuration in TaskAGI:

• In the Add Task to Sheet node, paste your Google Sheet URL in the sheet_url field
• Map each AI agent output field to the corresponding spreadsheet column
• Enable automatic timestamp for the "Created Date" column
• Configure conditional formatting in Google Sheets to highlight high-priority tasks

Configuration Steps

Step 1: Define Agent Information (Informational Nodes)

These three nodes establish the agent's identity and purpose:

Agent Name Options (core.workflow_note)

• Document the agent's name: "Project Manager Agent" or "Task Intake Bot"
• List alternative names your team might use to reference this agent
• This helps with documentation and team onboarding

Category & Industry (core.workflow_note)

• Specify the category: "Project Management" or "Operations"
• Note your industry: "Software Development", "Marketing", "Consulting", etc.
• This helps organize agents in your TaskAGI dashboard

About This Agent (core.workflow_note)

• Write a brief description: "Automatically captures project tasks through chat and logs them to Google Sheets"
• Include key capabilities and limitations
• This description appears when team members interact with the agent

Step 2: Configure the Chat Trigger

Node: Chat Trigger (trigger.chat)

This node activates your workflow when a user initiates a conversation:

• Trigger Type: Set to "Message Received" or "Keyword Match"
• Keywords: Define activation phrases like:
  • "create task"
  • "new project"
  • "add to backlog"
  • "@project-manager"
• Response Format: Choose "Conversational" for natural interaction
• Enable Context: Allow the agent to reference previous messages in the conversation

Step 3: Configure the Project Manager Agent

Node: Project Manager Agent (core.ai_agent)

This is the intelligent core of your workflow:

• Model Selection: Set to "gpt-4o-mini" (as specified)
• Prompt Configuration: The agent uses [[nodes.4.message]] which references the user's chat message
• System Prompt (recommended):

  You are a helpful Project Manager assistant. Your role is to:
  1. Ask clarifying questions to gather task details
  2. Confirm you have: task name, description, assignee, priority, and due date
  3. Be conversational and friendly
  4. Only proceed when you have sufficient information
  

• Temperature: Set to 0.7 for balanced creativity and consistency
• Max Tokens: Set to 500 to keep responses concise

Step 4: Configure the Conditional Logic

Node: Have All Info? (core.if_condition)

This node validates whether the agent has collected all necessary information:

• Condition Type: Set to "Custom Logic"
• Validation Rules: Check that these fields are populated:
  • Task name (required)
  • Description (required)
  • Assigned to (required)
  • Priority level (required)
  • Due date (required)
• True Path: Proceed to task creation (node 8)
• False Path: Request more information (node 7)

Step 5: Configure Information Request Response

Node: Get More Info (chat.respond)

Triggered when information is incomplete:

• Message Template:

  I need a bit more information to create this task. 
  Could you please provide: [list missing fields]
  

• Enable Follow-up: Allow the conversation to loop back to the agent
• Tone: Keep it helpful and non-judgmental

Step 6: Configure Google Sheets Integration

Node: Add Task to Sheet (googlesheets.appendRowFromUrl)

This node writes validated task data to your spreadsheet:

• Sheet URL: Paste your Google Sheet URL in the sheet_url field
  • Example: https://docs.google.com/spreadsheets/d/1ABC123XYZ/edit
• Column Mapping: Map agent outputs to spreadsheet columns:
  • task_name → Column A (Task Name)
  • description → Column B (Description)
  • assigned_to → Column C (Assigned To)
  • priority → Column D (Priority)
  • due_date → Column E (Due Date)
  • status → Column F (Status) - default to "New"
  • timestamp → Column G (Created Date)
• Append Mode: Set to "Add New Row" to preserve existing data

Step 7: Configure Completion Response

Node: Respond Complete (chat.respond)

Confirms successful task creation to the user:

• Success Message Template:

  ✅ Task created successfully!
  Task: [task_name]
  Assigned to: [assigned_to]
  Due: [due_date]
  
  I've added this to your project sheet.
  

• Include Details: Reference the specific task information created
• Offer Next Steps: Suggest creating another task or viewing the sheet

Testing Your Agent

Test Execution Steps

1. Initial Setup Verification

• Ensure all integrations show Connected status
• Verify Google Sheet URL is correctly entered
• Confirm chat platform is active and responsive

2. Run a Test Conversation

• Open your chat interface
• Type your activation keyword: "create task"
• Observe the agent's initial response
• Verify it asks for required information

3. Provide Complete Information

• Respond with all task details in one message:

  Task: Update user authentication
  Description: Implement OAuth 2.0 for login
  Assign to: Sarah Chen
  Priority: High
  Due: 2024-02-15
  

4. Verify Conditional Logic

• Check that the agent confirms it has all information
• Observe the workflow proceeding to task creation (not requesting more info)

5. Validate Google Sheets Integration

• Open your Google Sheet
• Verify a new row was appended with your test task
• Confirm all fields populated correctly
• Check that timestamps are accurate

6. Test Incomplete Information Scenario

• Start another test with partial information:

  Task: Fix login bug
  

• Verify the agent asks for missing fields
• Provide the missing information
• Confirm the task is created after all details are supplied

What to Verify at Each Step

Expected Results and Success Indicators

✅ Successful Workflow Execution:

• Agent responds within 2 seconds of trigger
• All required fields are collected through natural conversation
• Google Sheet updates automatically within 5 seconds
• User receives confirmation message with task details
• No duplicate rows in spreadsheet
• Timestamps are accurate and consistent

✅ Data Quality Indicators:

• All task names are non-empty and descriptive
• Assigned team members match your organization's roster
• Priority levels follow your standard (High/Medium/Low)
• Due dates are in valid format (YYYY-MM-DD)
• Status field defaults to "New" for all created tasks

🎯 Performance Benchmarks:

• Average task creation time: 30-60 seconds (vs. 5-10 minutes manual)
• Data accuracy rate: 99%+ (AI validation + human confirmation)
• Integration reliability: 99.9% uptime
• User adoption: Track usage metrics in TaskAGI dashboard

Congratulations! Your Project Manager Agent is now ready to transform how your team creates and tracks tasks. Start with a small pilot group, gather feedback, and scale across your organization. Happy automating! 🚀