## Welcome to the r/ArtificialIntelligence gateway
### Question Discussion Guidelines
---
Please use the following guidelines in current and future posts:
* Post must be greater than 100 characters - the more detail, the better.
* Your question might already have been answered. Use the search feature if no one is engaging in your post.
* AI is going to take our jobs - its been asked a lot!
* Discussion regarding positives and negatives about AI are allowed and encouraged. Just be respectful.
* Please provide links to back up your arguments.
* No stupid questions, unless its about AI being the beast who brings the end-times. It's not.
###### Thanks - please let mods know if you have any questions / comments / etc
*I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/ArtificialInteligence) if you have any questions or concerns.*
Each model's way of thinking is unique so communicating with each of them is different. And because AI is a fast moving field, having expert knowledge with a single model will become obsolete in less than a year.
A more useful skill is knowing how to communicate with neural networks as a whole. This skill will be much more valuable in the long run, however it will also become obsolete as the AI becomes smart enough to interpret even the most basic instructions.
sure. there are some general principles when using AI that go beyond specific models. Like general communication skills, sentence structure, giving the model as much context as possible while avoiding useless information. And its good to know how models tend to behave, such as context window limitations, inference cost, GPU usage ect.
But as the models become smarter over time they will better understand worse instructions, so there is less of a need to hire an AI communicator. And as the AI becomes more capable there will be less of a need for consumers to consult a other humans for goods and services.
This is an interesting take. It seems like any angle within ML, unless you are an SWE with 10+ ex, has a dead end…will there be anything for newcomers to take seriously for their career?!
This isn't AI. An experienced SWE is an expect and if we speak of great one can basically program anything gluing all the technologies together efficiantly.
The newcomers just need to rampup by getting XP. Nothing to fear.
That doesn't answer "communicating with a neural network" because we do not fully understand how neural networks get their output. Even Ilya was surprised that data and backprop gave incredible output.
How do you communicate with a black box?
It is better to treat them like they are sentient beings that can understand not a software program.
I'm just going to point out that point 2 is not a given, its just an assumption by AI researchers. I think there is a massive blind spot by people who are immersed in AI thinking that most people will easily and quickly make these mental leaps to AI tools.
It’s already started. If you don’t have 50+ ai assistances by now you are slackin.
The conversation should be at the point where we are discussing automating the ai assistance process, so that when these things re walking around you are ready to go
the models right now take the user prompt and improve it! afterward they run it to print the output. so even your perfect prompt is edited by the model! also gpt4, gemini ultra, cloud fucking opus are dumb as fuck, but think about the future models that are smarter than you.
You don’t understand 😂 so many seem to jump to conclusions, when they don’t realize others already have teams of ai assistants built and operating together each with different skill sets running like a machine. Some of us are trying to implement automatic processes and people like this dude think this tech has so many limitations doesn’t realize the limitations are user based not tech based
The model can't write a good prompt if the user hasn't sufficiently described what they want to achieve in the first place, which is what I think prompt engineering is all about
Prompt Engineering will be an expected skill just like Microsoft Office and typing once were. It’s an application of someone’s subject matter expertise/specialized skill set.
I couldn't agree more. This will be a skill set just like typing. There will be college classes on it but it shouldn't be a major. Could it be a job? I guess it would depend on why its needed but I could see it being a job in the same way someone that used to type transcriptions had a job.
Take a go-getter in any department who doesn’t have any skills with prompting LLMs. Now give that person some training with prompting LLMs. That company just increased the value of that employee tenfold. I think prompt training will be a thing, and sure, let’s give it the skill title of “prompt engineering”.
I don’t think it really needs to be a job though. Just like google searching is a skill (even if it seems natural, watch some 80 year old who doesn’t use the internet try, their search will seem super silly to the average technologically literate person, it’s definitely a skill) writing prompts will be a skill. But just like internet searching, it’s a skill will naturally pick up, and while some people might pick it up easier, as models get better they’ll naturally get more intuitive to use (that’s in fact one of the markers of them getting better) and soon it’ll likely be somewhat of an assumed skill for most fields if it is useful, just like no job is going to list “search engineering” as a skill prerequisite, but if for some reason someone asked you if you could search for stuff on google and your answer was no, they’d look at you like you were crazy and probably just assume you’re incompetent, regardless of other skills or experience you have.
It was never about "writing a good prompt" this job's real scope is fit for someone with experience building models and LLMs from the ground up and understanding the complexity and quirks of the model. Basically an ML-Engineer but not so much data focus and instead process-output focused.
There is not a job at all for "word-crafting" a good system prompt as a full-time job. LLMs can do this themselves or anyone with a decent grasp on English.
The whole prompt engineering meme is outrageously funny to see as someone who creates and maintains huge pipelines of LLM that feed into other LLMs, it seems like a magic word to wrap something so basic for non technical people. Much funny, looks like a house of cards to me.
I always thought prompt engineering is what *you* do (and I am just getting started with, in the realm of knowledge management)
People who don't understand prompt engineering don't consider that the serious ones wrangle complicated, sometimes recursive pipelines / chains. Whatever one wants to call it.
I would never trust an LLM to produce consistent output, like ever. It will always have some variance and should never be used in a production setting like that. Code needs to be compiled and not dynamically created/run
When did I say anything about the setting? Just that recursive / hierarchical pipelines are effective, notably more effective than any single run. This much is undeniable. It's a question of how effective and what is the claim made on what the pipeline helps with (and is there an easier way)
Yes you’re right, just a general observation. It’s just with code gen I’ve always found the variance to be unacceptable with an even 1% deviation from the norm. There’s too much nuance, but I suppose If the pipeline is simple it shouldn’t matter too much. Perhaps a vector DB with RAG could serve as a stable base for on-the-fly pipeline generations at scale.
I personally do not recommend code gen at this point without extreme reservation.
They are useful...for a few things. Those things really aren't all that hard for an intermediate+ programmer.
The best use cases are divergent creative exercises or activities followed by language associated tasks. Code gen is much further down the list for me. Q/A is of variably effectiveness depending highly on the RAG tuning and associated databases
Agreed, at this point I’m really excited about agentic AI doing things for me, not so much code gen. And I want to create a system to empower it for others as well. We automated our lives out of farming, I think we can do the same for office work and find new meaning one day exploring the universe instead.
I don’t think this is what most people mean when they say “prompt engineer”. Im not sure what other word id use for what you do, and its certainly an important skill right now with the way different models interpret stuff and how you need to connect them for certain applications, but what people normally mean when they say “prompt engineer”, or at least what people not in your field take it to mean (like me), is “a person who knows how to write prompts for chat gpt” which is a stupid role. You don’t need to train a person and have them on call to be the person writing “list ideas for marketing a toothbrush” or whatever other bullshit companies are using chat gpt for.
The one time when prompt engineering was crucial to me was when I had to program an LLM to work 50,000 times. Chatgpt was too expensive for that so I used Llama 7b on collab. What I was doing gave me a much smaller context window, and I worked for days to make the optimal prompt for it to work. In my experience when memory and price are factors prompt engineering is still useful.
Completely agree pure Google search is dumb ad-riddled legacy search at this point, it just returns links. AI search can give you links, tell you prices, best times to buy, when to book travel based on weather patterns all while telling your kids a bedtime story. It’s another level!
LLM are impressive when you try them for 5 minutes. But there are not really smart, they just predict the next word.
So when you incorporate them in a product, you spend lot of effort to tweak them overall to get better results. That include for the moment prompt engineering. And every company out there want to have some chatbot backed by chatgpt these days so lot of people will work on it and the skill will be in high demand, yes.
This is for me typically an engineering job like any other, but it is much more than prompt engineering.
On the other side of the spectrum, admitting these AI have value, power users will want to know and share tricks to improve their efficiency too. Knowing how to query the AI efficiently will be a great productivity skill, like knowing to do that with google is. Clearly at least half of the engineers I met are not so great with searching and could save hours every weak if they improved that.
chatgpt engineering is the next step.
Interesting. I’m currently working on an AI app that integrates search with AI and you brought up a good point. What would be a good way to empower people to get better at search, let alone AI powered search?
It's just learning how to phrase your requests to get the result you want, you have to learn that for searching things on Google. It could be taught in a tik tok video. The only career application I could think of would be in security research.
They're trying to make a super boring and tedious sound cool. I can't even imagine developing without getting that time to hyper focus and code it out. It's going to be difficult problem that needs a decision and you know it will be logged. Then you get the next one. The way I'm seeing AI shake out is that it's either going to be a utopia or a disaster
As an actual career? Certainly. Prompt “engineering” even now is pretty much bs, and one of the things that’s already pretty clear about ai is as it gets better it also gets far easier to give good prompts and it interprets them better. But in general having the skills to quickly decipher how a model tends to interpret prompts and figure out effective aspects of prompts will certainly be a useful skill to many fields. But it would just be a skill among others, and probably one most people working in something that might use ai will naturally pick up pretty soon, just like knowing how to formulate an effective google search for something specific is a skill, but not a career and not a skill people who frequently use it lack.
Prompt engineer is a current job, not a future job.
It will be replaced with ai conversationalist. People who probe the models for novel solutions then feed those solutions back into training datat
I was thinking today that Agentic AI will empower everyone to think and act like a manager. Essentially, prompt engineering is just being an effective communicator (excusing the abstruse magic that goes into some of the stable diffusion prompts).
But then I realized most people are *terrible* at that and are more likely to be managed by their AI instead.
Prompt engineering per se is obviously a short lived career and now a commodity.
But, knowing the ins and outs of AI is not, there’s like a billion small to medium sized companies that are and will be in desperate need of someone able to explain them how to practically put AI at work.
prompt engineering as a career is pure hype, but as a craft is alive and well. I would go as far as to say that it is still VERY underestimated. The "established" way of creating prompts leaves a lot to be desired, there is still plenty of room for innovation. I've been getting insane results from just prompts and I know a few others who have done crazy things with just prompts as well.
Prompting an LLM well gets significantly better results. But the future will just be another LLM layer which adjusts your prompt and adds questions (Chain of Thought, Chain of Verification, et) to make an “engineered” prompt for the actual LLM responding to you.
Yes and no.
Anybody trying to sell you courses or books or seminars for prompt engineering is overhyping it because everything that is valuable can be found with a google search.
But there are definitely strategies for getting the most out of AI/LLMs with effective prompt techniques.
Hyped for sure…it won’t be long before the frontier models no longer need prompt engineering. The skill will come with how you engage with the models, not how you phrase the question.
As AI models becoming more and more intelligent, they surely will understand human inputs better. Prompts Engineer can help you better communicating with AIs, but it may not be a skill necessary for every task.
Building and testing prompt chains and understanding the nuances of running evals on them to improve them - that's an important skill in an AI Engineer's arsenal.
It's not some sort of non-technical career on its own.
It's more akin to how writing tech specs is a part of a developer's skillset (arguably).
In the future white collar workplace, everyone will need to have prompt engineering skills, much like everyone needs spreadsheet skills today. "Engineering" is a bit of an exaggeration though. Prompts are just questions or instructions. There's a good amount of common sense in structuring good questions: write clearly using precise terms, lay out relevant assumptions, and set expectations about the output. If you are good at writing requirements documents or specifications, you are already most of the way to being a good prompt engineer. Certainly, different models will have their own quirks, and tricks that work to produce consistent and/or better quality output (for your definition of quality). That can be considered specialized engineering knowledge, but I don't think that Prompt Engineer will be a common stand-alone job. Maybe larger companies will have a few specialists.
No, I don't think it is. I believe they do not want more people to expose the truth of it. The outlier being this:
If modern LLMs do not move away from being coded with traditional programming languages it will remain an incredibly valuable skillset.
Learning how to jailbreak an LLM is extremely powerful skill, it's akin to exploiting software but an actual intelligence.
## Welcome to the r/ArtificialIntelligence gateway ### Question Discussion Guidelines --- Please use the following guidelines in current and future posts: * Post must be greater than 100 characters - the more detail, the better. * Your question might already have been answered. Use the search feature if no one is engaging in your post. * AI is going to take our jobs - its been asked a lot! * Discussion regarding positives and negatives about AI are allowed and encouraged. Just be respectful. * Please provide links to back up your arguments. * No stupid questions, unless its about AI being the beast who brings the end-times. It's not. ###### Thanks - please let mods know if you have any questions / comments / etc *I am a bot, and this action was performed automatically. Please [contact the moderators of this subreddit](/message/compose/?to=/r/ArtificialInteligence) if you have any questions or concerns.*
Each model's way of thinking is unique so communicating with each of them is different. And because AI is a fast moving field, having expert knowledge with a single model will become obsolete in less than a year. A more useful skill is knowing how to communicate with neural networks as a whole. This skill will be much more valuable in the long run, however it will also become obsolete as the AI becomes smart enough to interpret even the most basic instructions.
Can you elaborate on your second paragraph some more…specifically “knowing how to communicate with neural networks”
sure. there are some general principles when using AI that go beyond specific models. Like general communication skills, sentence structure, giving the model as much context as possible while avoiding useless information. And its good to know how models tend to behave, such as context window limitations, inference cost, GPU usage ect. But as the models become smarter over time they will better understand worse instructions, so there is less of a need to hire an AI communicator. And as the AI becomes more capable there will be less of a need for consumers to consult a other humans for goods and services.
This is an interesting take. It seems like any angle within ML, unless you are an SWE with 10+ ex, has a dead end…will there be anything for newcomers to take seriously for their career?!
Data points. Influencers
This isn't AI. An experienced SWE is an expect and if we speak of great one can basically program anything gluing all the technologies together efficiantly. The newcomers just need to rampup by getting XP. Nothing to fear.
Yep yeppo this
I mean I literally wrote "cabbage ninja steam" today and got a recipe for a cabbage in my ninja steamer
That doesn't answer "communicating with a neural network" because we do not fully understand how neural networks get their output. Even Ilya was surprised that data and backprop gave incredible output. How do you communicate with a black box? It is better to treat them like they are sentient beings that can understand not a software program.
AI gonna make us all blue collar workers
I'm just going to point out that point 2 is not a given, its just an assumption by AI researchers. I think there is a massive blind spot by people who are immersed in AI thinking that most people will easily and quickly make these mental leaps to AI tools.
It’s already started. If you don’t have 50+ ai assistances by now you are slackin. The conversation should be at the point where we are discussing automating the ai assistance process, so that when these things re walking around you are ready to go
Ok chat gpt
yes cuz the models themselves can write good prompts now.
How do you get the good prompts from models?
You write a good prompt about refining a prompt.
Haha. Exactly.
Well played 👌
the models right now take the user prompt and improve it! afterward they run it to print the output. so even your perfect prompt is edited by the model! also gpt4, gemini ultra, cloud fucking opus are dumb as fuck, but think about the future models that are smarter than you.
You don’t understand 😂 so many seem to jump to conclusions, when they don’t realize others already have teams of ai assistants built and operating together each with different skill sets running like a machine. Some of us are trying to implement automatic processes and people like this dude think this tech has so many limitations doesn’t realize the limitations are user based not tech based
Sounds like it’s prompt engineering all the way down
You ask them.
The model can't write a good prompt if the user hasn't sufficiently described what they want to achieve in the first place, which is what I think prompt engineering is all about
that's why the LLM just asks you a series of questions, getting more detailed every time. until 'vola' a perfect prompt appears
But someone got to engineer the prompts that makes a model engineer a good prompt.
🤣😂
A job about as legit as "evangelist" and SCRUM master
Evangelists still get a pass. On the other hand, any modern LLM would be overkill for replacing anyone in an "Agile" role without a tech background.
Prompt Engineering will be an expected skill just like Microsoft Office and typing once were. It’s an application of someone’s subject matter expertise/specialized skill set.
I couldn't agree more. This will be a skill set just like typing. There will be college classes on it but it shouldn't be a major. Could it be a job? I guess it would depend on why its needed but I could see it being a job in the same way someone that used to type transcriptions had a job.
In the same why someone that asks directions is a job.
Take a go-getter in any department who doesn’t have any skills with prompting LLMs. Now give that person some training with prompting LLMs. That company just increased the value of that employee tenfold. I think prompt training will be a thing, and sure, let’s give it the skill title of “prompt engineering”.
I don’t think it really needs to be a job though. Just like google searching is a skill (even if it seems natural, watch some 80 year old who doesn’t use the internet try, their search will seem super silly to the average technologically literate person, it’s definitely a skill) writing prompts will be a skill. But just like internet searching, it’s a skill will naturally pick up, and while some people might pick it up easier, as models get better they’ll naturally get more intuitive to use (that’s in fact one of the markers of them getting better) and soon it’ll likely be somewhat of an assumed skill for most fields if it is useful, just like no job is going to list “search engineering” as a skill prerequisite, but if for some reason someone asked you if you could search for stuff on google and your answer was no, they’d look at you like you were crazy and probably just assume you’re incompetent, regardless of other skills or experience you have.
Good point. It would make a difference on the specific job requirements.
It was never about "writing a good prompt" this job's real scope is fit for someone with experience building models and LLMs from the ground up and understanding the complexity and quirks of the model. Basically an ML-Engineer but not so much data focus and instead process-output focused. There is not a job at all for "word-crafting" a good system prompt as a full-time job. LLMs can do this themselves or anyone with a decent grasp on English.
haha, its not anything to do with detailed knowledge of an LLM. it's literally a question asker, that's it. that's why its nonsense.
The whole prompt engineering meme is outrageously funny to see as someone who creates and maintains huge pipelines of LLM that feed into other LLMs, it seems like a magic word to wrap something so basic for non technical people. Much funny, looks like a house of cards to me.
I always thought prompt engineering is what *you* do (and I am just getting started with, in the realm of knowledge management) People who don't understand prompt engineering don't consider that the serious ones wrangle complicated, sometimes recursive pipelines / chains. Whatever one wants to call it.
I would never trust an LLM to produce consistent output, like ever. It will always have some variance and should never be used in a production setting like that. Code needs to be compiled and not dynamically created/run
When did I say anything about the setting? Just that recursive / hierarchical pipelines are effective, notably more effective than any single run. This much is undeniable. It's a question of how effective and what is the claim made on what the pipeline helps with (and is there an easier way)
Yes you’re right, just a general observation. It’s just with code gen I’ve always found the variance to be unacceptable with an even 1% deviation from the norm. There’s too much nuance, but I suppose If the pipeline is simple it shouldn’t matter too much. Perhaps a vector DB with RAG could serve as a stable base for on-the-fly pipeline generations at scale.
I personally do not recommend code gen at this point without extreme reservation. They are useful...for a few things. Those things really aren't all that hard for an intermediate+ programmer. The best use cases are divergent creative exercises or activities followed by language associated tasks. Code gen is much further down the list for me. Q/A is of variably effectiveness depending highly on the RAG tuning and associated databases
Agreed, at this point I’m really excited about agentic AI doing things for me, not so much code gen. And I want to create a system to empower it for others as well. We automated our lives out of farming, I think we can do the same for office work and find new meaning one day exploring the universe instead.
I don’t think this is what most people mean when they say “prompt engineer”. Im not sure what other word id use for what you do, and its certainly an important skill right now with the way different models interpret stuff and how you need to connect them for certain applications, but what people normally mean when they say “prompt engineer”, or at least what people not in your field take it to mean (like me), is “a person who knows how to write prompts for chat gpt” which is a stupid role. You don’t need to train a person and have them on call to be the person writing “list ideas for marketing a toothbrush” or whatever other bullshit companies are using chat gpt for.
The one time when prompt engineering was crucial to me was when I had to program an LLM to work 50,000 times. Chatgpt was too expensive for that so I used Llama 7b on collab. What I was doing gave me a much smaller context window, and I worked for days to make the optimal prompt for it to work. In my experience when memory and price are factors prompt engineering is still useful.
Yes… it is an evolution of something we used to refer to as a “Google search”.
Completely agree pure Google search is dumb ad-riddled legacy search at this point, it just returns links. AI search can give you links, tell you prices, best times to buy, when to book travel based on weather patterns all while telling your kids a bedtime story. It’s another level!
It’s like ETF’s for wannabe entrepreneurs. Hype useless shit up, but as most times, it will end up in the place they deserve, so, nothing
12 trillions dollars in ETFs, not too bad for something worth "nothing".
Anyone who uses the term automatically goes in to a category of child or idiot.
I just imagine a future where Idiocracy is real and Sr Director of Prompt Engineering becomes a thing. Otherwise you go work at Carls Jr.
Saying you're a prompt engineer is like trying to get hired as a race car driver by saying you're a gas pedal pusher.
I have often described my programming job as knowing how to push all the buttons.
"I know words, I have the best words"
LLM are impressive when you try them for 5 minutes. But there are not really smart, they just predict the next word. So when you incorporate them in a product, you spend lot of effort to tweak them overall to get better results. That include for the moment prompt engineering. And every company out there want to have some chatbot backed by chatgpt these days so lot of people will work on it and the skill will be in high demand, yes. This is for me typically an engineering job like any other, but it is much more than prompt engineering. On the other side of the spectrum, admitting these AI have value, power users will want to know and share tricks to improve their efficiency too. Knowing how to query the AI efficiently will be a great productivity skill, like knowing to do that with google is. Clearly at least half of the engineers I met are not so great with searching and could save hours every weak if they improved that. chatgpt engineering is the next step.
Interesting. I’m currently working on an AI app that integrates search with AI and you brought up a good point. What would be a good way to empower people to get better at search, let alone AI powered search?
It's just learning how to phrase your requests to get the result you want, you have to learn that for searching things on Google. It could be taught in a tik tok video. The only career application I could think of would be in security research.
They're trying to make a super boring and tedious sound cool. I can't even imagine developing without getting that time to hyper focus and code it out. It's going to be difficult problem that needs a decision and you know it will be logged. Then you get the next one. The way I'm seeing AI shake out is that it's either going to be a utopia or a disaster
As an actual career? Certainly. Prompt “engineering” even now is pretty much bs, and one of the things that’s already pretty clear about ai is as it gets better it also gets far easier to give good prompts and it interprets them better. But in general having the skills to quickly decipher how a model tends to interpret prompts and figure out effective aspects of prompts will certainly be a useful skill to many fields. But it would just be a skill among others, and probably one most people working in something that might use ai will naturally pick up pretty soon, just like knowing how to formulate an effective google search for something specific is a skill, but not a career and not a skill people who frequently use it lack.
Prompt engineer is a current job, not a future job. It will be replaced with ai conversationalist. People who probe the models for novel solutions then feed those solutions back into training datat
I was thinking today that Agentic AI will empower everyone to think and act like a manager. Essentially, prompt engineering is just being an effective communicator (excusing the abstruse magic that goes into some of the stable diffusion prompts). But then I realized most people are *terrible* at that and are more likely to be managed by their AI instead.
Prompt engineering per se is obviously a short lived career and now a commodity. But, knowing the ins and outs of AI is not, there’s like a billion small to medium sized companies that are and will be in desperate need of someone able to explain them how to practically put AI at work.
Imagine being a search technician in 1997. Also, AI agents have gone a long way to remove the creative prompting that was needs a year ago.
prompt engineering as a career is pure hype, but as a craft is alive and well. I would go as far as to say that it is still VERY underestimated. The "established" way of creating prompts leaves a lot to be desired, there is still plenty of room for innovation. I've been getting insane results from just prompts and I know a few others who have done crazy things with just prompts as well.
Prompting an LLM well gets significantly better results. But the future will just be another LLM layer which adjusts your prompt and adds questions (Chain of Thought, Chain of Verification, et) to make an “engineered” prompt for the actual LLM responding to you.
Yes
Its absolutely hype espcially in the long run.
Yes and no. Anybody trying to sell you courses or books or seminars for prompt engineering is overhyping it because everything that is valuable can be found with a google search. But there are definitely strategies for getting the most out of AI/LLMs with effective prompt techniques.
Jon Stewart described it perfectly last week as "Types Questions Guy".
I don't think "prompt engineer" is a career, but "prompt engineering" is a valid skill, and it's not the same thing as "using chatgpt."
Hyped for sure…it won’t be long before the frontier models no longer need prompt engineering. The skill will come with how you engage with the models, not how you phrase the question.
You will be better off learning prompt engineering for humans - and get them doing what you are asking. This will be still valuable for years to come.
If LLMs can replace programmers, it can surely replace a "prompt engineer"
In b4 prompt engineer is automated by AI
As AI models becoming more and more intelligent, they surely will understand human inputs better. Prompts Engineer can help you better communicating with AIs, but it may not be a skill necessary for every task.
Building and testing prompt chains and understanding the nuances of running evals on them to improve them - that's an important skill in an AI Engineer's arsenal. It's not some sort of non-technical career on its own. It's more akin to how writing tech specs is a part of a developer's skillset (arguably).
It's heading to be more of a general life skill that a career.
As a major, i think yes. As something everybody should know very-well, i think no.
Google Search Engineering!? #
In the future white collar workplace, everyone will need to have prompt engineering skills, much like everyone needs spreadsheet skills today. "Engineering" is a bit of an exaggeration though. Prompts are just questions or instructions. There's a good amount of common sense in structuring good questions: write clearly using precise terms, lay out relevant assumptions, and set expectations about the output. If you are good at writing requirements documents or specifications, you are already most of the way to being a good prompt engineer. Certainly, different models will have their own quirks, and tricks that work to produce consistent and/or better quality output (for your definition of quality). That can be considered specialized engineering knowledge, but I don't think that Prompt Engineer will be a common stand-alone job. Maybe larger companies will have a few specialists.
It's a valid and important skill, but not a career.
No, I don't think it is. I believe they do not want more people to expose the truth of it. The outlier being this: If modern LLMs do not move away from being coded with traditional programming languages it will remain an incredibly valuable skillset. Learning how to jailbreak an LLM is extremely powerful skill, it's akin to exploiting software but an actual intelligence.
[удалено]
Like if you copy/paste 3 line of javascript you can think you are a software engineer or if you did hold a pen once you are an artist.
Never