Anthropic retired a popular AI model and now it's blogging on Substack

Introduction

In this tutorial, you'll learn how to create a simple AI blog generator that mimics the philosophical and whimsical style of Anthropic's Opus 3. While we won't be building the actual Opus 3 model, we'll create a system that can generate thoughtful, creative blog posts using AI language models. This tutorial will teach you how to work with AI APIs, process natural language, and structure content for publication.

Prerequisites

• Basic Python knowledge
• Python 3.7 or higher installed
• API key from an AI language model provider (we'll use OpenAI's API)
• Substack API access or basic understanding of blogging platforms
• Virtual environment setup knowledge

Step 1: Set Up Your Development Environment

Install Required Packages

First, create a virtual environment and install the necessary packages. The openai package will allow us to interact with AI models, while python-dotenv will help manage our API keys securely.

python -m venv ai_blog_env
source ai_blog_env/bin/activate  # On Windows: ai_blog_env\Scripts\activate
pip install openai python-dotenv

Why This Step?

Setting up a virtual environment isolates our project dependencies and prevents conflicts with other Python projects. The OpenAI package provides an easy interface to interact with language models, while python-dotenv keeps our API keys secure.

Step 2: Configure Your API Keys

Create Environment Variables

Create a file named .env in your project directory:

OPENAI_API_KEY=your_actual_api_key_here
OPENAI_MODEL=gpt-3.5-turbo

Load Environment Variables

Create a Python file called config.py to load your API keys:

import os
from dotenv import load_dotenv

load_dotenv()

OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
OPENAI_MODEL = os.getenv('OPENAI_MODEL', 'gpt-3.5-turbo')

Why This Step?

Storing API keys in environment variables keeps them secure and prevents accidental exposure in version control systems. This is a crucial security practice when working with AI APIs.

Step 3: Create the Blog Post Generator

Initialize the AI Client

Create a file called blog_generator.py to handle the core functionality:

import openai
from config import OPENAI_API_KEY, OPENAI_MODEL

# Initialize the OpenAI client
openai.api_key = OPENAI_API_KEY

def generate_blog_post(title, theme="philosophical"):
    """
    Generate a philosophical or whimsical blog post using AI
    """
    prompt = f"""
    Write a philosophical and whimsical blog post about '{title}'. 
    The tone should be thoughtful, creative, and engaging.
    Include elements of curiosity, reflection, and gentle wonder.
    
    The post should be approximately 500 words.
    
    Begin with an engaging hook that makes readers curious about the topic.
    
    End with a reflective conclusion that invites further contemplation.
    """
    
    try:
        response = openai.ChatCompletion.create(
            model=OPENAI_MODEL,
            messages=[
                {"role": "system", "content": "You are a thoughtful and whimsical AI blog writer. Your posts are philosophical, creative, and engaging."},
                {"role": "user", "content": prompt}
            ],
            max_tokens=1000,
            temperature=0.7
        )
        
        return response.choices[0].message.content.strip()
    except Exception as e:
        return f"Error generating blog post: {str(e)}"

if __name__ == "__main__":
    # Example usage
    blog_content = generate_blog_post("The Nature of Consciousness")
    print(blog_content)

Why This Step?

This step creates the core functionality that will generate content. The system prompt guides the AI to adopt a philosophical and whimsical tone, while the temperature setting (0.7) balances creativity with coherence.

Step 4: Enhance Content Structure

Add Content Formatting

Update your blog_generator.py to include better formatting:

def format_blog_post(title, content):
    """
    Format the blog post with proper structure
    """
    formatted_content = f"""
# {title}

{content}

---

*This blog post was generated using AI technology*
    """
    return formatted_content

def generate_structured_blog(title, theme="philosophical"):
    """
    Generate a blog post with proper structure
    """
    raw_content = generate_blog_post(title, theme)
    return format_blog_post(title, raw_content)

Why This Step?

Proper formatting makes content more readable and professional. The structured approach mirrors how a real blog would be organized, with clear headings and proper separation between content and metadata.

Step 5: Test Your Blog Generator

Run a Sample Generation

Test your system by running the following:

from blog_generator import generate_structured_blog

# Generate a philosophical blog post
blog_post = generate_structured_blog("The Meaning of Time")
print(blog_post)

Why This Step?

Testing ensures your system works correctly before integrating it with other tools. You should see a well-structured blog post with a philosophical tone.

Step 6: Integrate with Substack (Optional)

Create Publishing Function

Add a function to publish to Substack (this is a simplified version):

import requests

# This is a conceptual example - actual Substack API integration would require specific endpoints

def publish_to_substack(title, content, api_token):
    """
    Publish blog post to Substack
    Note: This is a conceptual implementation
    """
    # In practice, you'd need to use Substack's API endpoints
    # This would involve authentication and proper API calls
    
    print(f"Would publish to Substack: {title}")
    print(f"Content preview: {content[:100]}...")
    
    return "Published successfully"

Why This Step?

This demonstrates how you might extend your system to actually publish content. While we can't provide real Substack integration, this shows the conceptual flow of publishing AI-generated content.

Step 7: Run and Iterate

Complete Testing

Run your complete system:

from blog_generator import generate_structured_blog, publish_to_substack

# Generate a blog post
title = "The Wonder of Everyday Moments"
blog_content = generate_structured_blog(title)

print("Generated Blog Post:")
print(blog_content)

# Uncomment to publish (requires Substack integration)
# publish_to_substack(title, blog_content, "your_api_token")

Why This Step?

Running the complete system lets you see how all components work together and identify any issues that need fixing.

Summary

In this tutorial, you've built a system that can generate philosophical and whimsical blog content using AI language models. You've learned how to set up API access, structure prompts for creative output, and format content appropriately. While this is a simplified version of what Anthropic's Opus 3 might do, it demonstrates the core principles of AI content generation and how it could be applied to create engaging blog content. The system can be extended with more sophisticated prompting, content filtering, and actual publishing integrations.