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Ready to build your first AI agent? In this tutorial, you’ll create an autonomous data analyst that can fetch Bitcoin prices, analyze trends, and generate professional charts - all through simple chat commands. No coding experience required.

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What You’ll Build

AI agent Bitcoin price analysis chart showing year-over-year trends with Python matplotlib visualization By the end of this AI agent tutorial, you’ll have an autonomous agent that:
  • Fetches real-time financial data automatically
  • Analyzes trends using Python (pandas, matplotlib)
  • Generates professional visualizations
  • Works without any API keys or coding
Example task: “Analyze Bitcoin price trends over the last year and create a visualization” Time to complete: 2 minutes
Skill level: Beginner (no coding required)

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Prerequisites

Before you begin building your AI agent, make sure you have: That’s it. Splox handles API keys, infrastructure, and tool orchestration automatically.

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Step 1: Choose the DevOps Agent Template

  1. Navigate to the Templates page
  2. Find and click the DevOps Agent card (under Development category)
  3. On the template details page, click Use Template
The workflow canvas will open automatically with your new AI agent ready to use. What’s happening: Splox creates a pre-configured autonomous agent with all the tools needed for data analysis, file management, and code execution. Splox templates page showing DevOps Agent template for building AI agents DevOps Agent template details page with Use Template button to create AI agent Quick link: Open DevOps Agent template directly

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Step 2: Activate Chat Mode

In the bottom toolbar, click the chat bubble icon (5th icon from left). A chat panel will slide in from the right side of the screen. What’s happening: Chat Mode lets you interact with your AI agent using natural language - no need to configure nodes or write code. Chat Mode interface for interacting with AI agent using natural language

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Step 3: Give Your AI Agent a Task

In the chat input field at the bottom, type: 
Analyze Bitcoin price trends over the last year and create a visualization
Press Enter to send. What’s happening: The autonomous AI agent will automatically:
  1. Fetch Bitcoin price data from a public source
  2. Use Python (pandas/matplotlib) to analyze the data
  3. Generate a professional chart
  4. Save it as an image you can download

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Step 4: Watch Your AI Agent Work Autonomously

Your AI agent will immediately start working on the task. You’ll see:
  • Real-time tool usage in the chat (e.g., “Fetching data…”, “Running Python analysis…”)
  • Active nodes lighting up on the workflow canvas (left side)
  • Progress updates as the agent uses different tools
The analysis typically takes 1-2 minutes. What’s happening: The agent autonomously:
  1. Searches for reliable Bitcoin price data sources
  2. Fetches historical price data
  3. Writes and executes Python code (pandas, matplotlib)
  4. Generates a professional multi-chart visualization
  5. Saves and shares the result

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Step 5: Review Your AI-Generated Analysis

Once complete, the agent will respond with:
  • Detailed analysis of Bitcoin price trends
  • Key insights highlighting important patterns
  • Professional visualization embedded in the chat
  • Downloadable file (click the filename to save)
You can also see the Python code used by expanding the code blocks in the response. Complete AI-generated Bitcoin price analysis with professional chart and insights

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What You’ve Learned About Building AI Agents

  • How to create an autonomous AI agent using pre-built templates
  • Using Chat Mode to interact with agents naturally
  • Autonomous data fetching and analysis
  • Python code execution in secure sandboxes
  • Professional data visualization without coding

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Try These AI Agent Tasks Next

Now that you have a working AI agent, experiment with these tasks: Data Analysis:
  • “Compare Ethereum vs Bitcoin performance over 6 months”
  • “Analyze stock market trends for tech companies”
  • “Create a chart showing global temperature changes”
File Operations:
  • “Create a CSV with the top 10 programming languages and their popularity”
  • “Analyze this dataset and find outliers” (upload a file)
Web Research:
  • “Research and compare the top 5 AI companies by valuation”
  • “Find trending GitHub repositories this week”

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Frequently Asked Questions

No. Splox’s no-code platform lets you build autonomous AI agents using natural language. The agent handles all coding automatically.
The DevOps Agent template costs approximately $0.71/hour for the sandbox environment. AI model costs vary by provider. Check our pricing page for details.
Yes. You can modify the workflow canvas, add custom tools, integrate APIs, and configure the agent’s behavior through the visual editor.
AI agents can access public APIs, web data, uploaded files, databases, and connected services like Google Sheets, Airtable, and Notion.

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Next Steps in Your AI Agent Journey

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