SEO Machine

Open-source AI-powered content creation and optimization system built on Claude Code by Craig Hewitt (Castos founder). Automates the complete SEO content lifecycle—research, strategy, writing, and editing—to generate high-quality, ranking-focused content at scale.

Architecture & Technical Foundation

Command and Agent Structure

  • Commands – User-invoked workflows (e.g., /SEO-write [topic]) that execute specific tasks on demand
  • Agents – Background processes that continuously monitor and optimize content workflows
  • Context folders – Dedicated storage for brand voice, product features, customer information, and writing samples

Data Integration

Incorporates multiple sources to inform content decisions:

  • SEO data (Ahrefs, Data for SEO)
  • Google Analytics metrics
  • Google Search Console data
  • Readability scoring and keyword optimization
  • Competitive analysis and positioning

Capabilities & Workflow

Complete Content Lifecycle

  1. Research – Gathers SEO data, competitive analysis, and topic research
  2. Strategy – Develops content clusters and positioning aligned with business goals
  3. Writing – Generates long-form, optimized blog content using brand voice and messaging
  4. Editing – Refines output for clarity, SEO effectiveness, and brand consistency

Execution Model

When commands like /SEO-write "how to optimize your LinkedIn profile" are executed, the system automatically references integrated brand context—including value propositions, target customer profiles (ICP), product features, and messaging frameworks—to ensure content alignment.

The system performs same analytical steps a skilled human writer would execute, understanding how each article fits into broader content strategy.

Craig Hewitt expanded SEO Machine into a broader “Link Marketing Machine” applying same AI agent architecture to multiple channels:

  • Email marketing – Analytics and automation
  • Paid advertising – Performance tracking
  • Social media – Content and analytics
  • SEO – Foundation pillar

Entire marketing team structure built in ~15 minutes using Claude Code in planning mode, with AI automatically extracting context from existing repositories to configure specialized agents for each channel.

Key Features

  • Multi-channel integration – Single system orchestrating across content, email, ads, social
  • Context-aware generation – References brand guidelines and customer data automatically
  • Modular architecture – Extensible design allowing new agents and commands
  • Human editing workflow – AI-assisted rather than fully autonomous
  • Cost efficiency – Dramatically reduces manual content creation labor

Access & Distribution

Free, open-source project on GitHub, democratizing AI-augmented marketing for:

  • Founders and entrepreneurs
  • Content marketers
  • Marketing teams
  • Solo creators

Philosophy & Impact

Represents shift from manual content creation toward AI-augmented workflows where systems intelligently combine research, strategy, writing, and optimization into coherent, semi-autonomous processes.

Demonstrates practical application of Claude Code for building sophisticated marketing automation without requiring specialized ML expertise.