Technical RequirementsControlling AI output through prompt designGuiding AI with instructions, guardrails, and contextCrafting clear, specific, constrained promptsUsing few-shot prompting and chain-of-thought for reliable responsesUsing AI to improve your promptsPreventing hallucinations through RAGUnderstanding RAG and how it reduces hallucinationsUsing NotebookLM as an instant RAG databaseHow model selection affects hallucination rateUsing deep research for reliable informationManaging context length to avoid hallucinationsUnderstanding what happens when the limit is exceededManaging context effectivelyRecognizing context-limit hallucinationsBuilding your own local RAG databaseSetting up the projectUsing Codex or Claude CodeSetting up manuallyUnderstanding how the RAG system worksSummary