Welcome! 👋 This workshop will guide you through building your own AI-powered coding assistant — starting from a basic chatbot, and adding powerful tools like file reading, shell command execution, and code searching.
You don’t need to be an AI expert. Just follow along and build step-by-step!
🌐 Want a detailed overview? Check out the blog post: ghuntley.com/agent
By the end of this workshop, you’ll understand how to:
- ✅ Connect to the Anthropic Claude API
 - ✅ Build a simple AI chatbot
 - ✅ Add tools like reading files, editing code, and running commands
 - ✅ Handle tool requests and errors
 - ✅ Build an agent that gets smarter with each step
 
You’ll build 6 versions of a coding assistant.
Each version adds more features:
- Basic Chat — talk to Claude
 - File Reader — read code files
 - File Explorer — list files in folders
 - Command Runner — run shell commands
 - File Editor — modify files
 - Code Search — search your codebase with patterns
 
graph LR
    subgraph "Application Progression"
        A[chat.go<br/>Basic Chat] --> B[read.go<br/>+ File Reading]
        B --> C[list_files.go<br/>+ Directory Listing]
        C --> D[bash_tool.go<br/>+ Shell Commands]
        D --> E[edit_tool.go<br/>+ File Editing]
        E --> F[code_search_tool.go<br/>+ Code Search]
    end
    
    subgraph "Tool Capabilities"
        G[No Tools] --> H[read_file]
        H --> I[read_file<br/>list_files]
        I --> J[read_file<br/>list_files<br/>bash]
        J --> K[read_file<br/>list_files<br/>bash<br/>edit_file]
        K --> L[read_file<br/>list_files<br/>bash<br/>code_search]
    end
    
    A -.-> G
    B -.-> H
    C -.-> I
    D -.-> J
    E -.-> K
    F -.-> L
    At the end, you’ll end up with a powerful local developer assistant!
Each agent works like this:
- Waits for your input
 - Sends it to Claude
 - Claude may respond directly or ask to use a tool
 - The agent runs the tool (e.g., read a file)
 - Sends the result back to Claude
 - Claude gives you the final answer
 
We call this the event loop — it's like the agent's heartbeat.
graph TB
    subgraph "Agent Architecture"
        A[Agent] --> B[Anthropic Client]
        A --> C[Tool Registry]
        A --> D[getUserMessage Function]
        A --> E[Verbose Logging]
    end
    
    subgraph "Shared Event Loop"
        F[Start Chat Session] --> G[Get User Input]
        G --> H{Empty Input?}
        H -->|Yes| G
        H -->|No| I[Add to Conversation]
        I --> J[runInference]
        J --> K[Claude Response]
        K --> L{Tool Use?}
        L -->|No| M[Display Text]
        L -->|Yes| N[Execute Tools]
        N --> O[Collect Results]
        O --> P[Send Results to Claude]
        P --> J
        M --> G
    end
    
    subgraph "Tool Execution Loop"
        N --> Q[Find Tool by Name]
        Q --> R[Execute Tool Function]
        R --> S[Capture Result/Error]
        S --> T[Add to Tool Results]
        T --> U{More Tools?}
        U -->|Yes| Q
        U -->|No| O
    end
    - Go 1.24.2+ or devenv (recommended for easy setup)
 - An Anthropic API Key
 
Option 1: Recommended (using devenv)
devenv shell  # Loads everything you needOption 2: Manual setup
# Make sure Go is installed
go mod tidyexport ANTHROPIC_API_KEY="your-api-key-here"A simple chatbot that talks to Claude.
go run chat.go- ➡️ Try: “Hello!”
 - ➡️ Add 
--verboseto see detailed logs 
Now Claude can read files from your computer.
go run read.go- ➡️ Try: “Read fizzbuzz.js”
 
Lets Claude look around your directory.
go run list_files.go- ➡️ Try: “List all files in this folder”
 - ➡️ Try: “What’s in fizzbuzz.js?”
 
Allows Claude to run safe terminal commands.
go run bash_tool.go- ➡️ Try: “Run git status”
 - ➡️ Try: “List all .go files using bash”
 
Claude can now modify code, create files, and make changes.
go run edit_tool.go- ➡️ Try: “Create a Python hello world script”
 - ➡️ Try: “Add a comment to the top of fizzbuzz.js”
 
Use pattern search (powered by ripgrep).
go run code_search_tool.go- ➡️ Try: “Find all function definitions in Go files”
 - ➡️ Try: “Search for TODO comments”
 
fizzbuzz.js: for file reading and editingriddle.txt: a fun text file to exploreAGENT.md: info about the project environment
API key not working?
- Make sure it’s exported: 
echo $ANTHROPIC_API_KEY - Check your quota on Anthropic’s dashboard
 
Go errors?
- Run 
go mod tidy - Make sure you’re using Go 1.24.2 or later
 
Tool errors?
- Use 
--verbosefor full error logs - Check file paths and permissions
 
Environment issues?
- Use 
devenv shellto avoid config problems 
Tools are like plugins. You define:
- Name (e.g., 
read_file) - Input Schema (what info it needs)
 - Function (what it does)
 
Example tool definition in Go:
var ToolDefinition = ToolDefinition{
    Name:        "read_file",
    Description: "Reads the contents of a file",
    InputSchema: GenerateSchema[ReadFileInput](),
    Function:    ReadFile,
}Schema generation uses Go structs — so it’s easy to define and reuse.
| Phase | What to Focus On | 
|---|---|
| 1 | chat.go: API integration and response handling | 
| 2 | read.go: Tool system, schema generation | 
| 3 | list_files.go: Multiple tools, file system | 
| 4 | bash_tool.go: Shell execution, error capture | 
| 5 | edit_tool.go: File editing, safety checks | 
| 6 | code_search_tool.go: Pattern search, ripgrep | 
If you use devenv, it gives you:
- Go, Node, Python, Rust, .NET
 - Git and other dev tools
 
devenv shell   # Load everything
devenv test    # Run checks
hello          # Greeting scriptOnce you complete the workshop, try building:
- Custom tools (e.g., API caller, web scraper)
 - Tool chains (run tools in a sequence)
 - Memory features (remember things across sessions)
 - A web UI for your agent
 - Integration with other AI models
 
This workshop helps you:
- Understand agent architecture
 - Learn to build smart assistants
 - Grow capabilities step-by-step
 - Practice using Claude and Go together
 
Have fun exploring and building your own AI-powered tools! 💻✨
If you have questions or ideas, feel free to fork the repo, open issues, or connect with the community!