The reasoning models push the capabilities of GPT models further, allowing for better performance by thinking step by step.

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.

The longer models like GPT-3 are able to think through complex problems, the better they perform.

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

A model that combines the knowledge and intuition of GPT-4.5 with advanced reasoning capabilities would be exceptionally powerful, making GPT-4.5 a crucial bridge towards that future.

The future of prompting may involve more guided interactions with the model, rather than just typing into a text box.

There's a risk of overcomplicating prompts by trying to anticipate every possible issue the model might face, which can lead to ineffective results.

The distinction between model versions like GPT-4 and GPT-5 is becoming less clear, as continuous improvements blur the lines between iterations.

Current AI, including models like GPT-4, does not exhibit true intelligence; it makes mistakes that humans wouldn't, such as confidently stating incorrect numerical comparisons.