Almost everyone who uses ChatGPT, Claude, or any other AI model has run into this problem at some point: the AI gives you information that is just plain wrong. In this episode, Zareef breaks down a simple, practical approach to spotting and handling wrong information from LLMs, and why you need to stay in the driver's seat when it comes to quality control.

• Always take the AI disclaimer seriously, it can and will make mistakes
• Separate facts from reasoning, facts like dates or measurements are verifiable, reasoning is not the same thing
• Prompt the AI upfront to verify its own suggestions and check for conflicts with existing systems
• Always ask for sources, but never trust a source blindly, check if it's actually reliable
• Rely on primary sources whenever possible
• Ask the model to state its confidence level, but remember research shows AI tends to be more confident when it's wrong
• Challenge every answer, ask if it's sure, ask it to verify its own claims
• Do independent verification and check internal consistency
• Remember you are the quality control, not the AI
• Understand that AI is a next token generation system, not a fact machine
• Rely on AI for intelligence and capability, not as a source of guaranteed facts