We compare how we actually use ChatGPT (and Claude) every day and why most people treat LLMs more like a personal helper than a work automation tool. We dig into what happens to your data after you hit Enter, from memories and human review to cross-border storage and training settings. 

We cover several topics:

• Our top real-world use cases for ChatGPT and why they are mostly non-work 
• How ChatGPT memory works and what it can infer about you 
• The "asking, doing, expressing" framework and why “expressing” feels new (it's not something you've ever done with Google)
• What the under-26s' usage stats suggest about adoption and behaviour 
• Where your prompt data can be stored and why multiple jurisdictions can apply 
• Why companies keep multiple copies of data and what that means for control 
• How human-in-the-loop review works and how incredibly rare it is 
• The ChatGPT “improve the model for everyone” toggle and what opting out changes 
• Personality and tone settings in ChatGPT plus the risk of AI-fuelled echo chambers 

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