AI Agent
Build autonomous AI agents that call other apps and tools dynamically based on user input.
The AI Agent node represents a fundamental shift from traditional workflows to agentic workflows. Instead of you defining each step and input manually, the AI Agent autonomously decides which tools to use and how to fill their inputs based on the conversation context.
Think of it as transforming your workflow from a rigid sequence of predefined steps into an intelligent assistant that can dynamically choose and execute the right actions.
The AI Agent has a different visual structure compared to other nodes:
- Right handle: Connect to other nodes (like Send Message, Email, etc.) - works like any normal node
- Bottom handle: Connect AI Tools - this is unique to AI Agent and allows you to give the AI access to other Markifact nodes as tools it can call autonomously
This dual-handle design reflects its dual nature: it’s both a processing node (like others) and a tool coordinator (unique capability).
Traditional Workflow vs. Agentic Workflow
Traditional AI Workflow
- You define: Every input, every connection, every step
- AI role: Processes data you provide in a predetermined sequence
- Example: Trigger → Get GA4 Data → Analyze Data → Send Email
Agentic Workflow
- AI decides: Which tools to use, what inputs to provide, when to execute
- Your role: Provide high-level instructions and available tools
- Example: “Analyze our marketing performance” → AI autonomously pulls GA4 data, analyzes trends, and suggests actions
When to Use AI Agent
AI Agent excels at:
- Chatbots and conversational interfaces (Slack bots, customer support)
- Dynamic data analysis where the AI chooses relevant data sources
- Multi-step research tasks that require different tools based on findings
- Adaptive workflows that change based on user questions
Perfect Use Case: Slack Chatbot
Build a marketing assistant that responds to questions in Slack:
- Trigger: Slack → On New Message
- AI Agent: Process the message and decide what data to fetch
- Tools: GA4 Get Report, Google Ads Get Report, Meta Ads Get Report (as AI tools)
- Response: Slack → Send Channel Message
The AI automatically chooses which marketing platform to query based on the user’s question.
Key Features
✨ Smart Input Detection
Each input field shows a sparkle icon (✨) with the hint: “Leave empty if you want AI to set”
This means you can let the AI:
- Choose date ranges dynamically
- Select appropriate metrics
- Fill in contextual parameters
Conversation Memory
The Conversation ID maintains context across multiple messages:
- Links related messages (like Slack thread IDs)
- Remembers previous exchanges
- Treats new threads as fresh conversations
AI Tools Integration
Connect other Markifact nodes as “tools” that the AI can call:
- Not all nodes are available as AI tools yet (we’re rolling them out gradually)
- Click Add Tool to see currently available AI tools
- AI decides when and how to use each tool
Inputs
| Field | Type | Required | Description |
|---|---|---|---|
| Instructions | Dynamic Text Area | ✅ | High-level instructions for your AI agent (e.g., “You are a helpful marketing assistant”) |
| Message | Dynamic Text Area | ✅ | The user’s input or question that the agent should respond to |
| Model | Model Selector | ✅ | Choose your AI model (GPT-4.1 recommended for complex tool usage) |
| Conversation ID | Dynamic Text | ❌ | Unique identifier to maintain conversation history (use Slack thread_id, email conversation_id, etc.) |
| Schema Fields | Schema Builder | ❌ | Define structured output format if you need consistent data structure |
Example: Slack Marketing Bot
Here’s how to build a Slack bot that answers marketing questions:
Workflow Setup
Configuration
Instructions:
Message: Connect the message from your Slack trigger
Conversation ID: Connect the conversation ID from your Slack trigger for memory
User Interactions
User: “How did our Google Ads perform last week?” AI Agent: Automatically calls Google Ads Get Report tool, responds with insights
User: “Compare that to Meta Ads” (in same thread) AI Agent: Remembers previous context, calls Meta Ads Get Report, provides comparison
Memory and Context
The Conversation ID is crucial for maintaining context:
- Same Conversation ID: AI remembers previous exchanges, builds on context
- Different Conversation ID: Fresh start, no memory of previous conversations
- No Conversation ID: Each message is treated independently
This works for any platform - Slack threads, email conversations, or chat sessions.
Available AI Tools
You can see the list of available AI tools by clicking the Add AI Tool handle when configuring your AI Agent. The available tools are constantly expanding as we roll out more integrations.
Output
The AI Agent returns structured output that can include:
- Generated text response
- Data from called tools
- Structured fields (if schema is defined)
- Tool execution logs and results
Connect the output to:
- Slack/Teams: Send responses back to users
- Email: Send detailed reports
- Sheets: Log conversations and data
Credit Cost
Cost depends on the selected model. See the Credits & Usage page for details.
Also, for each tool called by the AI Agent, there may be additional costs based on the specific node’s credit usage (e.g., GA4 Get Report, Google Ads Get Report).
The total cost for an AI Agent run is the sum of the AI model cost and any tool costs incurred during execution.
Frequently Asked Questions
Why isn't my AI Agent remembering previous conversations?
Why isn't my AI Agent remembering previous conversations?
Check your Conversation ID setup:
- Make sure you’re connecting the Conversation ID from your trigger
- For Slack: Connect the conversation ID field from your Slack trigger
- For email: Connect the thread/conversation ID from your email trigger
- Missing Conversation ID = fresh conversation every time
Common mistakes:
- Forgetting to connect the Conversation ID field
- Using the wrong field from your trigger (like timestamp instead of conversation ID)
What's the difference between AI Tools and regular nodes?
What's the difference between AI Tools and regular nodes?
| Regular Nodes | AI Tools |
|---|---|
| You configure all inputs manually | AI fills inputs automatically based on context |
| Fixed execution order | AI decides when to use them |
| You connect them in sequence | AI calls them dynamically |
| Always execute | Only execute when AI deems necessary |
Example:
- Regular GA4 node: You set date range, metrics, dimensions
- GA4 AI Tool: AI decides what data to pull based on user’s question
Why can't I find certain nodes as AI Tools?
Why can't I find certain nodes as AI Tools?
We’re gradually rolling out nodes as AI tools because:
- Each node needs special AI integration
- Complex nodes require additional prompt engineering
- We prioritize the most commonly used nodes first
When should I use 'Select Accounts' vs pre-selecting my account?
When should I use 'Select Accounts' vs pre-selecting my account?
Use Select Accounts AI tool when:
- You want AI to choose the right account dynamically
- You have multiple ad accounts/properties
- User might ask about different accounts (“Show me data for our EU account”)
Pre-select your account when:
- You always want data from the same account
- You have only one account connected
- You want to limit AI to specific data sources
Example:
Why is my AI Agent slow or timing out?
Why is my AI Agent slow or timing out?
Common causes:
- Too many AI tools connected (AI tries to decide between many options)
- Large date ranges in data requests
- Complex instructions that confuse the AI
Solutions:
- Limit AI tools to what you actually need
- Use clear, specific instructions
- For heavy data tasks, consider pre-filtering with regular nodes
How do I make my AI Agent more accurate?
How do I make my AI Agent more accurate?
Better Instructions:
Model Selection:
- GPT-4.1: Best for complex tool usage
- GPT-4o: Faster for simple questions
- GPT-4.1 Mini: Cost-effective for basic tasks
How many tools should I connect?
How many tools should I connect?
Start small: 2-3 related tools (e.g., GA4 + Google Ads + Meta Ads)
Add gradually: Test behavior before adding more
Quality over quantity: Better to have 3 relevant tools than 10 confusing ones
Can I force AI Agent to use specific tools?
Can I force AI Agent to use specific tools?
In the message: “Use Google Ads data to show me…”
In instructions: “Always check GA4 first, then Google Ads if needed”
Pre-filtering: Use regular nodes before AI Agent for must-have data
What happens if a tool fails?
What happens if a tool fails?
AI Agent will:
- Try alternative approaches
- Inform you about the failure
- Provide partial results if possible
- Suggest manual steps if needed
Best practice: Test your tools individually before adding them to AI Agent.
Which AI model should I choose?
Which AI model should I choose?
GPT-4.1: Best for complex tool usage and detailed analysis, but slower and more expensive
GPT-4o: Good balance of speed and capability for most marketing tasks
GPT-4.1 Mini & Nano: Cost-effective and fast response times, ideal for:
- Simple questions and quick responses
- High-volume chatbot interactions
- Basic data queries
Recommendation: Start with GPT-4o for most use cases, upgrade to GPT-4.1 for complex analysis, or downgrade to Mini/Nano for speed and cost savings.
Why is my AI Agent taking a long time to respond?
Why is my AI Agent taking a long time to respond?
Response time depends on the AI model you’re using, not Markifact:
Model Processing Times:
- GPT-4.1: Slower but most capable, especially when running Python code for calculations
- GPT-4o: Moderate speed with good capabilities
- Mini/Nano: Fastest response times
What slows down responses:
- Complex tool usage requiring multiple API calls
- Python code execution for data analysis
- Large datasets being processed
- Multiple tools being evaluated
To speed up responses:
- Use Mini or Nano models for simple questions
- Limit the number of connected AI tools
- Use more specific instructions to reduce decision time
Why do I see 'This is a test message' when I run my Slack AI Agent?
Why do I see 'This is a test message' when I run my Slack AI Agent?
This happens when you click the Run button in the Markifact UI to test a workflow with a Slack trigger.
Why it shows: Since your workflow starts with “Slack: On New Message,” there’s no actual Slack message when you test manually, so Markifact shows this placeholder.
How to test properly:
- Activate your workflow by clicking the switch button at the top
- Go to Slack and mention your bot:
@markifact how did our ads perform? - Check the History/Runs tab to see if your message was received
Alternative testing method:
- Temporarily remove the Slack message input from AI Agent
- Write your test message manually in the Message field
- Test using the Run button
- Reconnect the Slack message input when ready to go live
I sent a message on Slack but nothing happens. Why?
I sent a message on Slack but nothing happens. Why?
Most common issues:
1. Workflow not active
- Check if the workflow switch is turned ON (top right)
- Inactive workflows don’t respond to triggers
2. Wrong channel configuration
- Your Slack trigger might be set to listen only to specific channels
- Check your “On New Message” trigger settings
- Make sure you’re messaging in the correct channel
3. Bot not mentioned
- Some configurations require mentioning the bot:
@markifact - Try both with and without mentioning the bot
How to troubleshoot:
- Go to History/Runs tab to see if the message was received
- Check if the workflow triggered at all
- Look at the logs to see where it might have stopped
My AI Agent is sending multiple responses to the same message. Why?
My AI Agent is sending multiple responses to the same message. Why?
This happens when you have multiple workflows with the same Slack trigger responding to the same channel.
Solutions:
Option 1: Use different channels
- Set up each AI Agent for different Slack channels
- Example: #marketing-reports, #ad-performance, #analytics
Option 2: Combine into one workflow
- Use one AI Agent with multiple tools
- Let the AI decide which tools to use based on the question
- More efficient and avoids duplicate responses
Option 3: Add channel filters
- Configure each workflow’s Slack trigger to listen to specific channels only
- This prevents overlap between different AI Agents
Best practice: One AI Agent per channel, or one comprehensive AI Agent with all needed tools.