To get the most out of them you have to provide context. Treat these models like some kind of eager beaver junior engineer who wants to jump in and write code without asking questions. Force it to ask questions (eg: “do not write code yet, please restate my requirements to make sure we are in alignment. Are there any extra bits of context or information that would help? I will tell you when to write code”)

If your model / chat app has the ability to always inject some kind of pre-prompt make sure to add something like “please do not jump to writing code. If this was a coding interview and you jumped to writing code without asking questions and clarifying requirements you’d fail”.

At the top of all your source files include a comment with the file name and path. If you have a project on one of these services add an artifact that is the directory tree (“tree —-gitignore” is my goto). This helps “unaided” chats get a sense of what documents they are looking at.

And also, it’s a professional bullshitter so don’t trust it with large scale code changes that rely on some language / library feature you don’t have personal experience with. It can send you down a path where the entire assumption that something was possible turns out to be false.

Does it seek like a lot of work? Yes. Am I actually more productive with the tool than without? Probably. But it sure as shit isn’t “free” in terms of time spent providing context. I think the more I use these models, the more I get a sense of what it is good at and what is going to be a waste of time.

Long story short, prompting is everything. These things aren’t mind readers (and worse they forget everything in each new session)