Why Does AI Still Miss the Point?

[Bulk Digital Store]

AI can produce impressive results, but getting it to follow our exact requirements is still a challenge. Even with detailed prompts, the output may differ from what we actually expect.

Is it a prompting issue, or is AI still not precise enough? What’s your experience?

 

[cromie]

AI can produce impressive results, but getting it to follow our exact requirements is still a challenge. Even with detailed prompts, the output may differ from what we actually expect.

Is it a prompting issue, or is AI still not precise enough? What’s your experience?

it is imo, a combination of the two. while better prompts will certainly produce better results, the AI may sometimes overlook some tiny details or understand our instructions differently from what we actually meant. even a really good prompt may sometimes require a few changes to produce an appropriate ressult.

 

[WebRankX]

I think it can be both. Sometimes the prompt is not clear enough, but even with a good prompt, AI can still miss small details.
I usually treat the first output as a starting point and refine it from there.

 

[thaaz]

A detailed prompt isn’t always a clear specification. If fifteen requirements are buried inside one long paragraph, the model can follow most of them and still miss the one you cared about. Id turn the important requirements into a short checklist, include an example of an acceptable result, then ask it to review its own output against that list. It still wont be perfect, but at least you can see exactly which requirement failed

 

[LOQ Marketing Agency]

Sometimes you use the same command, but at different times, and people will get different results. I think this is because everyone can easily synthesize updated information from various sources to create and answer that question, so the results can't be 100% the same and accurate.

 

[Bulk Digital Store]

Sometimes you use the same command, but at different times, and people will get different results. I think this is because everyone can easily synthesize updated information from various sources to create and answer that question, so the results can't be 100% the same and accurate.

Exactly. The same prompt can produce different results depending on the timing, available data, and sources being synthesized. That’s why results may vary and aren’t always 100% identical or accurate.

 

[gomatsu]

Don’t use it to provide you with finalized content, I use it to fluff up details on a certain subject and then rewrite to make it sound more human-like.

 

[cosmoaccs]

AI can produce impressive results, but getting it to follow our exact requirements is still a challenge. Even with detailed prompts, the output may differ from what we actually expect.

Is it a prompting issue, or is AI still not precise enough? What’s your experience?

this is the exact thing that drives me nuts sometimes ngl i can write a super detailed prompt, be all specific, n it still comes back lookin nothin like what i pictured in my head. feels like theres always a gap between what i meant and what it understood

i do think its partly a prompting skill thing, like the more u learn how to structure it (context, constraints, examples, negative prompts) the closer u get. but theres def also a limit to how precise these models can be, theyre still probabalistic at the end of the day not exact calculators

question tho — when u run into this, do u usually try to fix it by tweaking the prompt over n over, or do u just accept the result n work around it? and how many retries do u give it before u say screw it genuinely curious cuz i feel like my patience varies alot depending on the day

 

[peter37calzo]

That's the real issue with Ai, no matter the prompt you used it will still be missing something that you actually want.

 

[ClivoraX]

I think the clear prompts helps a lot but even then AI can miss small details I usually need to fix the output after.

 

[Siennaia]

AI can produce impressive results, but getting it to follow our exact requirements is still a challenge. Even with detailed prompts, the output may differ from what we actually expect.

Is it a prompting issue, or is AI still not precise enough? What’s your experience?

It is both imo. the better the prompt, the less you miss, but the ai may understand the prompt in its own way. Therefore, I consider the first output to be the draft.

 

[serenareid]

I tested AI content for a small SEO project using the same prompt but changing how I structured the requirements. The version with examples and a fixed output format followed the brief much better. Still, it occasionally ignored small constraints like word count or keyword placement. Interestingly, adding more instructions actually made some outputs worse.

 

[X39Rank]

I think AI works better when you give it examples. Showing what you want can be easier than explaining everything in text.

 

[Nishkka]

AI can produce impressive results, but getting it to follow our exact requirements is still a challenge. Even with detailed prompts, the output may differ from what we actually expect.

Is it a prompting issue, or is AI still not precise enough? What’s your experience?

Ex: are useful however, I usually regard the first output as a draft. even with the great prompt, there is always a possibility that the ai will miss some little point nd hence manual editing take less time.

 

[willowsia]

AI can produce impressive results, but getting it to follow our exact requirements is still a challenge. Even with detailed prompts, the output may differ from what we actually expect.

Is it a prompting issue, or is AI still not precise enough? What’s your experience?

Imo, it is both, but examples would do better rather than instruction. Imo, it is a draft, and I modify it according to my need

 

[fansgurus001]

I think it’s a mix of both. Better prompts definitely improve the results, but AI still struggles with very specific requirements. I usually get better results by breaking the task into smaller steps instead of asking for everything in one prompt.

 

[CarlosTheGaucho]

The concept of machine learning can produce impressive results, but only with something, where there is a sufficient amount of high quality, exact data, to use as a data source for generating the answer.

My original education is cybernetics and biomedical engenering, I've known AI and the concept of machine learning 20 years before everyone started to talk about it and use it ,after it was made available to public.

Aka there's a major difference between:

1) Find a numerical pattern from the data sheet attached (objective and using exact data that won't allow for alternative reasoning)

2) Create this and this to look based on these requirements (subjective and using instructions specified in the AI model and additional public available input data)

Moreover, in many cases it is possible to produce scenarios only, not an exact answer.

 

[dvc]

What's your use case? Coding? Content? Operations? Give more details and someone might help.

I would say that a combination of prompting, skills, integrations and good context will get you perfect results. Ofc, today, ai still cant oneshot any substantial task (despite what gurus says) but it can with multiple iterations get you exactly what you want.

 

[SEO Sparton]

Generally, it’s both. Better questions help, but AI still requires human intervention when accuracy and context are important.

 

[BlackShield]

I think it's a bit of both. Better prompts and clear context can improve consistency, but AI still isn't perfectly deterministic.

I've found the best results come from clear requirements + examples + constraints + iterative checking rather than expecting one perfect prompt to produce the exact output always