Karen Spinner successfully built a Minimum Viable Product (MVP) for a Substack newsletter digest tool in just 5 days, addressing the widespread problem of content overwhelm among active Substack users who struggle to keep up with high-quality subscriptions. She deliberately chose familiar technologies (Python/Django, PostgreSQL, Bootstrap) and a proven development process using Anthropic's Console rather than experimenting with newer AI coding tools, prioritizing speed and functionality over design polish. The MVP includes core features like newsletter import/management, adjustable digest settings, and automated article categorization, while intentionally deferring advanced features to gather user feedback quickly before investing in extensive development.

This article presents a comprehensive system prompt guide for creating an AI tutor specialized in teaching Python for cybersecurity and ethical hacking applications. The guide structures an AI instructor persona with 15+ years of expertise who teaches hands-on scripting for reconnaissance, exploitation, and defense while maintaining strict ethical boundaries and legal compliance. The curriculum covers 8 modules ranging from foundations and packet sniffing to defensive scripting and real-world projects, emphasizing safe, simulated learning environments and responsible disclosure practices throughout the instruction process.

A System Prompt Notebook (SPN) is a structured template method for achieving consistent, high-quality AI outputs by replacing placeholder brackets with specific project details, constraints, and examples before uploading to an AI model. The process involves a six-step cycle: filling out the template with concrete details, saving versioned files, uploading to the LLM with specific instructions, requesting outputs based on SPN requirements, reviewing results against criteria, and iteratively refining the SPN for improved performance. This approach helps prevent "prompt drift" and creates repeatable AI instructions that can be versioned and reused across projects.