[kelseyfrog]

> The quality of the model “operator” makes a massive difference in the outcomes.

My hunch is that this is the source of much of the variability in outcomes upstream of HN commenters claiming extremes of, "This model changes everything!" to "This[same] model is crap."

We haven't operationalized what it means to "be good at prompting," nor developed proxies/heuristics/shibboleths for accessing prompting skill. There's community skepticism over whether prompting skill even exists. Besides even if prompting skill is real, who wants to hear, "Actually you kinda suck at prompting."

[danielmarkbruce]

It's 100% this. Many people suck at prompting. It's likely that habits from search are ingrained. But in general some people are just so bad at it .

[jyounker]

Prompting is just writing specification documents. A lot of people are very bad at this. I suppose that more to the point, a lot of people are just bad at writing.

[danielmarkbruce]

This is probably correct. Perhaps prompting just brings out the very worst in specification.

[latexr]

According to Google, “there’s no wrong way to prompt”.

https://www.youtube.com/watch?v=9bBfYX8X5aU&t=48s

[knollimar]

No wrong way to [consume thing I sell that you'll consume more of if you do it poorly]

[djeastm]

Ehhh, their incentive in their marketing is to get normal people to not be intimidated by the big bad AI.

Power users are always going to have to take the messaging companies send out to the masses with a grain of salt.

[FireCrack]

IDK if it's just me, but I also find Claude, whether it be the model or the harness, is a lot more "forgiving" of poor prompts than many of the open models