It takes work, and breaking your problem down into very simple and clear tasks. It is possible to get decent data transformations from gpt 3.5 though. I generally start with gpt4 when prototyping an idea, and then after it's working consistently, I'll ask gpt4 to break the instructions down into smaller pieces. Even if it takes two or three runs through GPT 3.5 to get the full output transformed with what GPT4 could do in a single pass, it's still cheaper...
I believe they were referring to GPT-3.5, but yes, you can get it to be pretty successful at more complex tasks this way. You can also manually break the problem down yourself too, if itβs a standard workflow. So for example, rather than ask it to translate some text, summarize it, and classify it in a single prompt, doing it as 3 separate prompts that feed into one another is far more likely to be successful.
