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Tip beginner

Use Role Prompting for Expertise

Assign a specific expert role to the model (e.g., 'You are a senior database architect with 20 years of PostgreSQL experience'). Role prompting activates domain-specific knowledge patterns and produces more authoritative, detailed responses than generic prompts.

role-promptingexpertisepersonas

Tip advanced

Never Trust LLM Output as Safe Code

Never execute LLM-generated code in a privileged environment without sandboxing. Use containers, restricted runtimes, or code review gates to prevent generated code from accessing filesystems, networks, or databases it should not touch.

securitysandboxingcode-executionsafety

Tutorial Advanced

Creating a Custom RAG System

Retrieval Augmented Generation (RAG) combines the knowledge of LLMs with specific document retrieval. To build a basic RAG system: 1) Process your documents into embeddings, 2) Store them in a vector database, 3) When queried, retrieve relevant content based on similarity, 4) Augment your prompt with this content, and 5) Generate contextually informed responses.

Estimated time: 30 minutes

ragvector databaseembeddings

Tip Advanced