It does not have to be brushed away as "brute force" necessarily. We can, and do, build more reliable systems out of less reliable components. In fact, most industrial engineering accepts some defect rate and builds margins around it.

Software is no different. Even without AI, you already have buggy compilers and buggy OSes and buggy libraries. You just tend to accept the risk because you have some idea of what the failure modes are and can work around it or manage the risk in some other way (buy literal insurance.)

There are other places where some process has an error rate and you make up for that error rate by doing the work more than once and then comparing results. For example, I've heard in a video that satellites and other space craft often have 3 or 4 processors and compare the results to make sure there were no errors due to radiation. Similarly, we have RAID arrays that store data multiple times because disks can fail. So, even if AI has a failure rate of like 20%, maybe you can make up for that by running the same prompt multiple times with slight variations or with different models, comparing the results and choosing the best.

they are right. bad output is user error. there, am i suiting the role appropriately? i do like 65% believe that, fwiw.

> Was that ever actually shown to be effective? Is it still?

Yes! Personas demonstrated measurable improvement in a few different ways, with caveats of course. The common intuition is that personas influence token space in beneficial ways.

I'll come back here later on desktop and link a few (still) relevant papers on this topic.

I remember there were some studies that this kind of thing was effective a year or so ago, so essentially a lifetime in Model years.

However to me it seems completely reasonable that it would work, because my understanding of what happens is the model interprets what you said as:

Look for a group of people who are considered to be expert growth hackers by the world at large and answer my questions as though they were answering them.

So assuming that there are a set of questions that can best be answered by people that most other people identify as expert growth hackers then yes, I believe assigning a personality in this way should obviously work.

There was a time when stuff like "Unreal Engine, trending on ArtStation, 8K resolution" actually worked when prompting image gen models because such labels actually correlated with higher-quality images in the web-crawled training datasets available back then.

It reminds me when people would stuff their image prompts with things like NO DEFORMED FINGERS.

I've always wondered if the go-to should have been prefilling its response with "I am an expert growth leader, and here are my thoughts:".

The reason it seems suspicious is that it's phrased in a way that's oriented towards humans. I haven't tested this, but I suspect you'd get similar results if you said something like "orient your response to that of a growth hacker." Either one is likely to have the desired effect on the stochastic result.

I feel it helps for the personality aspect, how it handles answers and general vocabulary, but it doesn’t in any way improve skill level, at least that’s my take from building an assistant.

At least in the beginning of spicy autocomplete, this sort of role-play did work pretty dramatically at aligning a conversation to a task, though I don't think anyone ever tested it versus somewhat less cringe priming.

After that, cargo cults do what they do best.

They spin up agents, and then give them roles like commenter, and director of quality for the commenter. Although I'm unsure how the director helps since I've never seen one do actual work.

Commenting more than I should, to be honest.

I have a few periods during my daily routine where I’m waiting somewhere away from the computer and need a break from email.

A lot of my comments have double digit upvotes and some get into the mid hundreds. I try to actually read articles and provide thoughtful comments, which gets upvoted a lot more than the throwaway.

> Are you averaging like 2000+ comments a month?

52000 / 3 years would be under 1500 points per month or 48 points per day. That could be done with 1-2 helpful comments per day on popular threads.

3 pages deep into their comment history only brings me to 5 days ago so probably yes.