[jrexilius]

The first part of this, where you told it to ask YOU questions, rather than laboriously building prompts and context yourself was the magic ticket for me. And I doubt I would have stumbled on that sorta inverse logic on my own. Really great write up!

[danphilibin]

This is the key to a lot of my workflows as well. I'll usually tack some form of "ask me up to 5 questions to improve your understanding of what I'm trying to do here" onto the end of my initial messages. Over time I've noticed patterns in information I tend to leave out which has helped me improve my initial prompts, plus it often gets me thinking about aspects I hadn't considered yet.

[daxfohl]

Frankly getting used to doing this may help our communication with other engineers as well.

[fragmede]

promo from L5->L7 confirmed.

[daxfohl]

The big question is, which level will be replaced by GPT first?

[treetalker]

Indeed!

The example prompts are useful. They not only reduced the activation energy required for me to start installing this habit in my personal workflows, but also inspired the notion that I can build a library of good prompts and easily implement them by turning them into TextExpander snippets.

P.S.: Extra credit for the Insane Clown Posse reference!

[CamperBob2]

That's one of the key wins with o1-pro's deep research feature. The first thing it tends to do after you send a new prompt is ask you several questions, and they tend to be good ones.

One idea I really like here is asking the model to generate a todo list.

[nijaru]

I add something like “ask me any clarifying questions” to my my initial prompts. For larger requests, it seems to start a dialogue of refinement before providing solutions.

[theturtle32]

Can confirm, this is an excellent tactic when working with LLMs!