Comprehensive guides and best practices for using Large Language Models effectively and responsibly
Master the art of crafting effective prompts to get the best results from AI language models
Why prompt quality matters and its impact on AI outputs
Step-by-step guide to writing clear, specific prompts
Understanding how LLMs process and reason through problems
Techniques to activate deeper analytical thinking
Using AI to challenge assumptions and explore alternatives
How LLMs can interact with external tools and APIs
Teaching by example for consistent output patterns
Control creativity and randomness in AI responses
Reusable structures for common tasks and workflows
Optimize context window usage for long conversations
Enhance LLM responses with external knowledge sources
Working with text, images, and other media types
Using LLMs to analyze and interpret data
Best practices for AI-assisted content creation
Structure responses in JSON, markdown, and more
Crafting prompts for AI image generation tools
Identifying and preventing AI-generated inaccuracies
Protecting against prompt injection and misuse
Navigate regulatory requirements and industry best practices when using AI in regulated sectors
Using LLMs with protected health information
European data protection requirements for AI
California privacy law and AI with consumer data
Security and trust when using AI with customer data
Protecting payment card data in AI workflows
Federal requirements for LLM use in government agencies
Why classified data must never enter commercial LLMs
GLBA, SOX, FINRA, and banking regulations for LLMs
Protecting privilege and confidentiality with AI
Student privacy requirements for LLMs in education
Integrate LLMs into automated workflows using N8N, Zapier, and Make to supercharge your business processes
Overview of automation platforms and why they're powerful for AI
N8N vs Zapier vs Make: features, pricing, and trade-offs
Installation, setup, and your first AI workflow
Create your first Zap with AI in minutes
Build visual AI workflows with Make's intuitive interface
Proven patterns for triage, extraction, generation, and more
Build resilient workflows that handle failures gracefully
Process multiple items efficiently in N8N, Zapier, and Make