AI Tools Best Practices Essentials

What we verified before publishing

AI-generated content may contain mistakes. Check the sources below before relying on important information.

The following claims were verified through Perplexity Sonar before the questions were finalised. The host can reference any of them during play:

• Generative AI is a type of artificial intelligence capable of creating original content such as text, images, audio, or software code in response to user prompts.
• A prompt is a piece of text, instruction, or input provided to an AI system to trigger a specific response or action from the model.
• Prompt engineering is the practice of crafting, refining, and optimizing inputs to guide generative AI models toward producing more accurate and relevant outputs.
• AI hallucination occurs when a generative AI model produces a response that is factually incorrect, nonsensical, or fabricated while presenting it as fact.
• Human-in-the-loop (HITL) is an architectural pattern where human oversight is integrated into AI workflows to provide feedback, verify decisions, or ensure safety.
• To protect data privacy, users should avoid sharing sensitive information like social security numbers, financial records, or confidential credentials with public AI tools.
• Data anonymization involves removing or masking personally identifiable information (PII) from datasets before using them with AI tools to reduce privacy risks.
• Many AI platforms may store user inputs to train or improve their models, so users should review privacy policies and opt-out settings if available.
• Multi-factor authentication (MFA) provides an essential layer of security for AI tool accounts, reducing the risk of unauthorized access to sensitive workflows.
• Effective AI workflows often benefit from clear task objectives, clean and structured data, and continuous monitoring to ensure accuracy and performance.