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From Ghost to Hugo: How GitHub Copilot Transformed My Blog Migration

A comprehensive look at using AI-powered development tools to seamlessly migrate from Ghost CMS to Hugo static site generator, complete with automated deployment to Azure.

Introduction

When I decided to migrate my blog from Ghost CMS to Hugo, I knew it would involve multiple complex steps: content conversion, theme selection, deployment setup, and countless configuration tweaks. What I didn’t expect was how GitHub Copilot would transform this potentially weeks-long project into a seamless, guided experience completed in a single afternoon.

This post chronicles the complete migration journey and highlights the specific ways AI-powered development assistance made the difference between a tedious manual process and an efficient, learning-rich experience.

The Migration Challenge

What We Started With

  • Ghost CMS: 11 published blog posts with rich content
  • Custom domain: www.ducksource.blog
  • Images and media: Embedded images requiring migration
  • SEO considerations: Preserving URLs and metadata
  • Deployment requirements: Automated CI/CD pipeline

What We Needed to Achieve

  • Hugo static site: Modern, fast static site generator
  • Theme selection: Professional, responsive design
  • Content preservation: All posts, images, and metadata intact
  • Custom branding: Personal avatar and logo integration
  • Production deployment: Azure Static Web Apps with custom domain
  • Automated workflow: GitHub Actions for continuous deployment

How GitHub Copilot Made the Difference

1. Intelligent Project Setup

Traditional Approach: Hours researching Hugo installation, theme selection, and configuration syntax.

With GitHub Copilot:

  • Instant Hugo project initialization with best practices
  • Intelligent theme recommendations based on requirements
  • Automatic configuration file generation with proper syntax
  • Real-time validation and error correction
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# Generated instantly with proper structure and comments
baseURL = "https://www.ducksource.blog/"
languageCode = "en-us"
title = "Ducksource"
theme = "stack"

[params]
  mainSections = ["post"]
  featuredImageField = "image"
  rssFullContent = true

2. Automated Content Migration

The Challenge: Converting Ghost’s JSON export to Hugo-compatible Markdown files.

AI Solution: GitHub Copilot generated a complete Python script that:

  • Parsed the Ghost JSON export intelligently
  • Converted HTML content to clean Markdown
  • Preserved all metadata (dates, tags, categories)
  • Generated proper Hugo frontmatter
  • Handled edge cases and malformed content
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# AI-generated conversion script (excerpt)
def convert_ghost_to_hugo(ghost_json_path, output_dir):
    """Convert Ghost blog export to Hugo markdown files"""
    with open(ghost_json_path, 'r', encoding='utf-8') as f:
        data = json.load(f)
    
    posts = data['db'][0]['data']['posts']
    
    for post in posts:
        if post['status'] == 'published':
            # Intelligent content processing
            markdown_content = html2text.html2text(post['html'])
            # ... smart frontmatter generation

3. Theme Customization and Branding

Traditional Process: Manual template editing, CSS customization, trial and error.

AI-Accelerated Process:

  • Intelligent theme comparison and recommendation
  • Automated avatar integration from LinkedIn profile
  • Custom logo creation and positioning
  • Template override generation with pixel-perfect positioning

The AI understood the request to “overlay the duck logo on the bottom right of the bio picture” and generated precise CSS positioning:

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.article-details .author-info .avatar::after {
    content: '';
    position: absolute;
    bottom: -5px;
    right: -5px;
    width: 40px;
    height: 40px;
    background: url('/img/duck-logo.svg') no-repeat center;
    background-size: contain;
}

4. Deployment Infrastructure as Code

The Request: “Set up Azure Static Web Apps with GitHub Actions”

AI Response: Complete infrastructure deployment including:

  • Azure Bicep templates for resource creation
  • GitHub Actions workflow with Hugo build steps
  • Custom domain configuration
  • SSL certificate automation
  • Deployment troubleshooting and optimization

5. Real-Time Problem Solving

When deployment issues arose (404 errors, workflow failures), GitHub Copilot:

  • Analyzed error logs and identified root causes
  • Suggested specific configuration fixes
  • Implemented solutions with precise file modifications
  • Validated fixes and monitored deployment success

Key Benefits Realized

1. Dramatic Time Savings

  • Estimated manual effort: 2-3 weeks
  • Actual completion time: Single afternoon session
  • Learning curve acceleration: Immediate best practices adoption

2. Error Prevention and Quality

  • Syntax validation in real-time
  • Best practice enforcement
  • Security considerations built-in
  • Performance optimizations included

3. Knowledge Transfer

  • Every solution came with explanations
  • Understanding of Hugo architecture gained
  • Azure deployment concepts learned
  • Git workflow mastery achieved

4. Professional Results

  • Production-ready deployment pipeline
  • Optimized performance and SEO
  • Responsive design across devices
  • Proper CI/CD automation

Specific GitHub Copilot Features That Excelled

Context Awareness

GitHub Copilot maintained context across the entire session, understanding:

  • Project structure and dependencies
  • Previous configurations and decisions
  • Error patterns and resolution history
  • User preferences and requirements

Multi-Technology Integration

Seamlessly worked across:

  • Hugo static site generation
  • Python scripting for content migration
  • Azure infrastructure deployment
  • Git workflow management
  • DNS and domain configuration

Iterative Problem Solving

When issues arose:

  • Analyzed symptoms intelligently
  • Proposed targeted solutions
  • Implemented fixes with precision
  • Validated results automatically

Lessons Learned

1. AI as a Force Multiplier

GitHub Copilot didn’t replace technical knowledge but amplified it dramatically. Complex tasks became approachable, and learning happened in context.

2. The Power of Conversational Development

Being able to describe goals in natural language (“I want to overlay the duck logo on the bio picture”) and receive working code solutions revolutionizes the development experience.

3. Quality Through AI Guidance

The resulting infrastructure follows best practices I might have missed in manual implementation - proper error handling, security configurations, and performance optimizations.

4. Reduced Context Switching

Instead of constantly researching documentation, Stack Overflow, and tutorials, development flow remained uninterrupted with AI providing just-in-time knowledge.

The Technical Stack Achievement

By the end of our session, we had deployed:

  • Hugo 0.150.0 static site with Stack theme
  • 11 migrated blog posts with preserved content and metadata
  • Custom branding with LinkedIn avatar and duck logo overlay
  • Azure Static Web Apps hosting in West Europe
  • GitHub Actions CI/CD with automated Hugo builds
  • Custom domain (www.ducksource.blog) with SSL
  • Responsive design optimized for all devices

Looking Forward: AI-Powered Content Creation

This migration experience has opened new possibilities for AI-assisted content creation and blog management. Future posts will explore:

  • Using AI for content ideation and research
  • Automated SEO optimization with GitHub Copilot
  • Performance monitoring and optimization workflows
  • Advanced Hugo features and customizations

Conclusion

The migration from Ghost to Hugo, aided by GitHub Copilot, demonstrated the transformative potential of AI-powered development tools. What traditionally requires extensive research, trial-and-error, and manual configuration became an efficient, educational, and enjoyable experience.

The key insight: AI tools like GitHub Copilot don’t replace developer expertise—they amplify it. They handle routine tasks, suggest best practices, and provide instant access to specialized knowledge, allowing developers to focus on creative problem-solving and strategic decisions.

For anyone considering similar migrations or complex technical projects, the combination of clear goal articulation and AI assistance can turn daunting challenges into achievable, well-executed solutions.

This post was written on the newly migrated Hugo site, deployed to Azure Static Web Apps, and published through the GitHub Actions workflow—all set up with GitHub Copilot assistance in a single afternoon.

Technical Details

Migration Tools Used:

  • GitHub Copilot for development assistance
  • Hugo v0.150.0 static site generator
  • Python scripts for content conversion
  • Azure Static Web Apps for hosting
  • GitHub Actions for CI/CD
  • Stack theme for Hugo

Repository: chriscoveyduck/ducksource-blog (Private)

Live Site: www.ducksource.blog