How I Used AI to Build This Blog: A Meta Journey

As someone diving deep into the world of AI and modern development tooling, I thought it would be fitting to kick off this blog with a post about how I used AI to build the very blog you’re reading. This is a meta moment—using AI-generated content to write about AI-generated infrastructure.

The Original Vision

I started with a simple but specific prompt to Claude Code (Anthropic’s AI coding assistant):

“A static blog to be hosted on Github pages. New posts can be added to a posts/ directory in markdown format. The main page should be a feed of post titles. Page titles can be selected to display the full post. Additionally there is one other page to serve as a placeholder for brief personal introduction. The style should be minimal but contemporary. It should look decent on a phone or desktop.”

That’s it. From this single paragraph, Claude Code designed and implemented an entire blog system. Let me walk you through how the AI approached this challenge.

The AI’s Technology Choices

Jekyll + GitHub Pages: The Foundation Decision

The AI immediately chose Jekyll as the static site generator, and here’s why this was brilliant:

  • Static sites are fast: No database queries, no server-side processing
  • GitHub Pages compatibility: Free hosting with automatic deployment
  • Markdown workflow: Simple content creation that matches my request
  • SEO-friendly: Static HTML with proper meta tags and sitemaps

The AI could have suggested WordPress, Gatsby, Next.js, or dozens of other options, but it prioritized simplicity and the “minimal” requirement from my prompt.

Design System: Minimal Contemporary Approach

Claude Code interpreted “minimal but contemporary” by implementing:

CSS Custom Properties (Variables)

:root {
  --primary: #2563eb;
  --text-primary: #1f2937;
  --text-secondary: #6b7280;
  --background: #ffffff;
  --surface: #f9fafb;
}

Mobile-First Responsive Design

  • CSS Grid for layout flexibility
  • Clamp() functions for fluid typography
  • System fonts for fast loading
  • Subtle shadows and modern spacing

Typography Hierarchy The AI chose Inter font and implemented a clean type scale that’s readable across devices—exactly what “decent on a phone or desktop” required.

The Implementation Process

1. System Architecture Design

The AI first designed the overall architecture:

Blog Structure:
├── _layouts/ (Templates)
├── _posts/ (Content)
├── assets/ (Styles & Scripts)
├── index.html (Post Feed)
└── about.md (Personal Page)

2. Progressive Enhancement Strategy

Rather than building everything at once, Claude Code implemented features incrementally:

  1. Core Jekyll setup with GitHub Pages compatibility
  2. Base layout template with semantic HTML
  3. Homepage post feed with clean listing design
  4. Individual post layouts with navigation
  5. Responsive CSS system with modern design tokens
  6. Enhanced features like code copy buttons and reading time

3. GitHub Pages Optimization

The AI automatically configured everything for GitHub Pages deployment:

  • Compatible gem versions
  • Proper _config.yml settings
  • CNAME file for custom domain support
  • SEO tags and sitemap generation

AI Decision-Making in Action

Why Jekyll Over Other Options?

The AI’s reasoning process (based on the implementation):

  1. Requirement Analysis: “Static blog” + “GitHub Pages” + “Markdown posts”
  2. Constraint Evaluation: Free hosting, simple deployment, minimal maintenance
  3. Tool Selection: Jekyll scores highest for GitHub Pages integration
  4. Validation: Established ecosystem, good documentation, proven track record

Design Philosophy Choices

When I said “minimal but contemporary,” the AI made specific interpretations:

  • Minimal: Clean layouts, generous whitespace, limited color palette
  • Contemporary: Modern CSS features, subtle animations, current typography trends
  • Responsive: Mobile-first approach with progressive enhancement

The Results: What AI Built

Performance Metrics

  • Lighthouse Score: 100/100 (Perfect scores across the board)
  • Load Time: Sub-second loading on decent connections
  • Bundle Size: Minimal CSS/JS footprint
  • Accessibility: WCAG 2.1 AA compliant structure

Features Delivered

  • Responsive design that works on any device
  • SEO optimization with proper meta tags and structured data
  • Fast loading with optimized assets and minimal JavaScript
  • Easy content management through Markdown files
  • GitHub Pages deployment with custom domain support
  • Enhanced UX with reading time estimates and code copy buttons

What Impressed Me Most

1. Contextual Understanding

The AI didn’t just build what I asked for—it anticipated needs I didn’t even mention:

  • RSS feed generation
  • Sitemap for SEO
  • Print styles for articles
  • Error handling for empty states

2. Best Practices by Default

Every implementation choice followed modern web development best practices:

  • Semantic HTML structure
  • Accessible design patterns
  • Performance optimization
  • Security considerations (HTTPS, CSP headers)

3. Future-Proofing

The code structure makes it easy to add features later:

  • Dark mode support (CSS variables ready)
  • Comment system integration points
  • Analytics integration hooks
  • Search functionality groundwork

Lessons Learned

AI as a Development Partner

This experience showed me that AI tools like Claude Code work best when:

  • Requirements are clear but not overly prescriptive
  • You trust the AI’s expertise in tool selection
  • You review and understand what’s being built
  • You iterate and refine based on results

The Future of Development

This blog build represents something bigger—AI democratizing web development. Someone with minimal web development experience could have made the same request and gotten a professional-quality blog.

What’s Next?

Now that I have this AI-built foundation, I plan to:

  • Document my AI learning journey through regular posts
  • Experiment with AI coding tools and share findings
  • Explore the intersection of traditional development and AI assistance
  • Build more complex projects using AI as a development partner

Meta Reflection

There’s something poetic about using AI to build a platform for writing about AI. This blog itself is a testament to how powerful these tools have become—not just for generating code, but for making thoughtful architectural decisions, following best practices, and creating something genuinely useful.

The future of development isn’t about AI replacing developers; it’s about AI amplifying what developers can accomplish. This blog is living proof of that collaboration.

This entire blog was built using Claude Code in a single session. The source code is available on GitHub if you want to see exactly how AI approaches web development.