In the future, prompting may involve the model eliciting information from us rather than us having to specify everything.

The future of human-computer interaction may involve more intuitive methods, such as speaking or even thinking commands, rather than traditional typing.

Chain of thought prompting, where you instruct the model to think step-by-step, is less necessary with modern reasoning models but can still be useful in some cases. If you're running thousands or millions of inputs through your prompt, you'll still need to use classical prompting techniques to make your prompt more robust.

Writing prompts for AI is becoming outdated; in the future, users will likely communicate with AI through more intuitive means, such as images or voice, rather than lengthy text prompts.

The prompt box in AI interfaces is crucial, and providing pre-built prompts can enhance user experience by guiding them in their input.

Reading prompts and model outputs closely helps improve prompting skills; experimentation is key.

When prompting, it's important to give the model an 'out' for unexpected inputs, allowing it to indicate uncertainty when necessary.

Using a larger model for meta prompting can yield better prompts that are then distilled into smaller models for practical use.

Feedback mechanisms in AI interfaces can help users refine their prompts and improve interaction with the AI, enhancing the overall experience.