Prompt engineering is dead but there is a better life after death.

Summary

In this insightful presentation from AI 5050, Bob Alink challenges traditional prompt engineering methods, advocating for a deeper understanding of AI's capabilities. He introduces 'prology,' a blend of technical and psychological knowledge, to master AI prompts effectively. Alink emphasizes the importance of asking AI questions to avoid assumptions and achieve non-average results. He showcases creative prompting techniques, such as using regional nuances and psychological frameworks, to harness generative AI's full potential, ultimately urging professionals to delve deeper into AI models for exceptional outcomes.

Takeaways

• 🔄 The presenter, Bob Alink, emphasizes the need to 'turn the world upside down' and look at AI from a different perspective to avoid average results.
• 🤖 He criticizes the current approach to 'prompt engineering' in 2024, likening it to the outdated practices of 1924, where people tried to extract information and enforce their will on others.
• 📚 Bob dismisses cheat sheets and shortcuts as ineffective, suggesting that they are based on assumptions rather than a true understanding of AI's capabilities.
• 🧑‍💼 He points out the misuse of roles and frameworks in AI, where people assign roles to AI without fully understanding what those roles entail or how to effectively use them.
• 🔍 Bob introduces the concept of 'prology', a blend of prompt engineering and psychology, as a way to deeply understand and interact with AI models.
• 📝 He advocates for asking AI models questions about their processes, rather than just giving commands, to gain insights into how they interpret and act on prompts.
• 🌐 The script discusses the importance of specifying regional contexts when prompting AI to avoid stereotypes and to tailor responses appropriately.
• 🌈 Bob highlights the potential of generative AI to create unique combinations of ideas and techniques that have not been previously combined, emphasizing the role of human creativity in this process.
• 📈 He provides examples of how to use AI for specific tasks, such as creating brand voice profiles or adapting text for low-literacy audiences, by asking the model to explain its actions.
• 🚀 The presenter encourages the audience to think creatively and to combine different psychological models and techniques in AI to achieve better results.
• 🛠️ Bob acknowledges the challenges of evolving AI models, which require ongoing learning and adaptation of prompting techniques to maintain effectiveness.

Q & A

What is the main theme of Bob Alink's presentation at AI 5050?

The main theme of Bob Alink's presentation is exploring new perspectives on how AI is influencing the world and the concept of 'prompt engineering', which he believes is flawed and needs to be rethought.

Why did Bob Alink start his presentation standing upside down?

Bob Alink started his presentation standing upside down to symbolize the idea that if AI is turning the world upside down, he needs to look at it from a different, less conventional perspective.

What does Bob Alink think about the use of cheat sheets and shortcuts in prompt engineering?

Bob Alink considers cheat sheets and shortcuts to be worthless, as they are based on assumptions and do not truly reflect the capabilities or the workings of AI.

What is Bob Alink's opinion on the use of roles in AI prompting?

Bob Alink believes that using roles in AI prompting without understanding what the template or role actually does can lead to assumptions and ineffective results.

What does Bob Alink propose as an alternative to traditional prompt engineering?

Bob Alink proposes 'prology', a combination of prompt engineering and prompt psychology, as an alternative approach to better understand and utilize AI.

What does Bob Alink mean by 'average is the new AI'?

By 'average is the new AI', Bob Alink is referring to the phenomenon where AI, when used by everyone in the same way, tends to produce average results, rather than exceptional or unique outcomes.

What technique does Bob Alink suggest to gain deeper insights into AI's understanding and use of prompts?

Bob Alink suggests using the 'what will you do' technique, where instead of executing a prompt, one asks the AI to explain what it would do with the prompt, to gain deeper insights.

How does Bob Alink approach the issue of AI's stereotypical responses?

Bob Alink addresses AI's stereotypical responses by explicitly instructing the AI to avoid stereotypes and to consider regional and cultural nuances in its responses.

Outlines

00:00

🔥 Challenging AI Prompt Engineering Norms

Bob Alink discusses the limitations of traditional AI prompt engineering, comparing the current state to the 1920s where people sought to extract and enforce information. He criticizes the use of cheat sheets and assumptions in prompting, advocating for a deeper understanding of AI's capabilities. Bob introduces the concept of 'prology', a blend of technical knowledge and communication psychology, to master AI prompts effectively. He emphasizes the need to ask questions and understand AI's true actions to escape average results and achieve exceptional outcomes.

05:00

🗣️ The Art of Talking to AI: Prology

This paragraph delves into the concept of prology, where Bob explains the importance of communicating with AI effectively. He suggests that the way we prompt AI now is flawed, as we often assume the AI understands our intentions without verifying. Bob introduces the idea of asking AI questions to understand its processes better, which he believes is crucial for learning how AI interprets and acts on prompts. He shares his personal journey of discovery with AI, emphasizing the need for creativity and logical sense in understanding AI's behavior.

10:03

🌐 Cultural Nuances in AI Prompting

Bob highlights the importance of considering cultural and regional nuances when prompting AI, using the example of how AI defaults to an American accent despite being prompted in different languages. He suggests that specifying the region can lead to more accurate and culturally sensitive responses. Bob also touches on the use of roles in prompts, recommending that including the country with the role can significantly improve the AI's output by avoiding stereotypes and tailoring the response to the specific cultural context.

15:05

📝 Exploring the Depth of AI Prompt Interpretation

In this paragraph, Bob explores the intricacies of how AI interprets different words in prompts, such as 'generate', 'make', 'create', and 'craft'. He demonstrates that these words can elicit different responses from the AI, depending on the context. Bob encourages users to experiment with various words and ask the AI to explain the differences in its actions. This approach can lead to a deeper understanding of AI behavior and, ultimately, more effective prompting.

20:07

🎨 Breaking Away from Average AI Results

Bob discusses the concept of 'average' AI results and how to transcend them through deeper prompting and creativity. He emphasizes that as AI evolves, it learns from the average user, which can limit its potential for creative and unique outputs. To counter this, Bob suggests using more specific and creative prompts, combining elements that have never been combined before, which he refers to as generative AI. This approach requires human creativity and can lead to more colorful and diverse AI outputs.

25:08

🤝 Combining Psychological Models for Enhanced AI Outputs

This paragraph focuses on the use of psychological marketing frameworks to enhance AI outputs. Bob mentions several psychological models and principles, such as Cini's principles and the FAB model, and suggests that combining these can lead to more effective AI responses. He also discusses the importance of asking the AI about the feasibility and effects of combining different models, which can result in unique and powerful AI applications.

30:10

🛠️ Mastering AI with Creative and Analytical Prompting

Bob shares his experience in creating detailed voice and style profiles for AI using up to 80 elements, which allows him to control the output of any text. He discusses the challenges and time investment required to master AI prompting, emphasizing the need for creativity, logical and analytical thinking. Bob also touches on the evolution of AI models and the necessity to continually adapt and deepen one's understanding of AI to maintain control over its outputs.

🚀 The Evolution of AI and Continuous Learning

In the final paragraph, Bob addresses the ongoing evolution of AI and the need for continuous learning and adaptation. He mentions the emergence of new AI models and the potential for previous prompts to become less effective over time. Bob encourages the use of creative thinking and the development of new prompts that combine novel elements. He also highlights the potential of AI agents and the importance of personal involvement in creating and optimizing prompts to achieve exceptional results.

Keywords

💡Prompt Engineering

Prompt Engineering refers to the technique of formulating questions or statements ('prompts') to guide an AI model to produce a specific output. In the video, it is discussed as a method that needs to evolve, as current practices often result in average outcomes. The speaker criticizes the assumption-driven approach and advocates for a deeper understanding of how AI interprets prompts.

💡Average Results

The term 'average results' in the script denotes the common, mediocre outcomes that AI systems produce when they are used in a conventional manner. The speaker argues that by using AI in the same way as everyone else, one is likely to get average results, which is not desirable for those seeking excellence or uniqueness in their work.

💡Roles

In the context of the video, 'roles' are templates or predefined sets of characteristics that users assign to AI models to simulate specific professional behaviors, such as a copywriter or a marketeer. The speaker points out that people often misuse roles without understanding their true impact, leading to ineffective prompting.

💡Frameworks

Frameworks are structured approaches or systems used to organize and guide the development of something, such as an AI model's output. The speaker warns against the blind use of frameworks without understanding their components and the AI's response to them, suggesting that a solid understanding of prompts is necessary before effectively using frameworks.

💡Prolology

Prolology is a term coined in the video to describe the combination of prompt engineering and prompt psychology. It involves not only understanding the technical aspects of constructing prompts but also having insight into the AI's behavior and communication. The speaker positions himself as a 'prolist,' someone who practices prolology, aiming to master AI through deeper questioning and understanding.

💡Generative AI

Generative AI is a concept in the video that refers to the creative use of AI to produce novel combinations of ideas or content that have not been previously associated. The speaker admires generative AI for its potential to enhance human creativity and produce unique outcomes, as opposed to the average results of conventional AI use.

💡False Friends

False friends are words that are similar in two languages but have different meanings, which can cause confusion, especially for individuals with low literacy in those languages. In the script, the speaker discusses using AI to identify and replace false friends in texts to cater to specific audiences, such as Nigerian English speakers, as an example of generative AI in action.

💡Non-Stereotypical

The term 'non-stereotypical' is used in the video to describe prompts that avoid common cliches or assumptions about certain roles or regions. The speaker suggests using AI to create outputs that are culturally sensitive and avoid stereotypes, such as a 'non-stereotypical French Belgium copywriter,' to achieve more authentic and relevant results.

💡Curiosity Gap

Curiosity Gap is a marketing technique that involves creating a sense of mystery or incomplete information to pique the audience's interest. The speaker explores using AI to craft titles that create a curiosity gap, suggesting that the choice of wording in prompts (e.g., 'craft' vs. 'generate') can influence the effectiveness of the outcome.

💡Marketing Psychology

Marketing Psychology involves understanding human behavior and decision-making processes to influence marketing strategies. The speaker mentions various psychological models and principles, such as Cialdini's principles and the work of other psychologists, which can be integrated into AI prompts to create more effective marketing content.

💡Evolution

In the context of the video, 'evolution' refers to the continuous development and improvement of AI models. The speaker notes that as AI evolves, the prompts that were effective in the past may not work in the same way with newer models, necessitating a deeper understanding and adaptation of prompting techniques to maintain optimal results.

Highlights

The presenter, Bob Alink, emphasizes the need to look at AI from a different perspective, suggesting that traditional prompt engineering is insufficient.

Alink criticizes the common practice of prompt engineering, comparing cheat sheets and assumptions to worthless shortcuts.

He introduces the concept of 'prology', a blend of prompt engineering and psychology, to better understand AI's response to prompts.

Alink advocates for more in-depth questioning of AI models to grasp how they interpret and execute prompts.

The idea that AI models can be influenced by specifying regions or countries to avoid stereotypical responses is discussed.

Alink demonstrates how different wording in prompts, such as 'generate' vs. 'craft', can lead to distinct AI behaviors.

The presenter suggests that generative AI can produce more creative and less average results by combining elements in new ways.

Alink explains how to use AI for tasks like creating low-literacy friendly texts and avoiding 'false friends' in different languages.

The importance of combining psychological marketing frameworks with AI to achieve targeted outcomes is highlighted.

Alink showcases the creation of detailed voice and style profiles using up to 80 elements for precise AI text control.

The evolution of AI models is addressed, noting that as they develop, professionals must adapt their prompting strategies.

The presenter discusses the use of 'what will you do' technique to gain insights into AI's interpretation of prompts.

Alink illustrates the power of three-word prompts in marketing, leveraging psychological principles for impact.

He emphasizes the need for creativity and deep understanding to harness generative AI's full potential.

Alink provides examples of how to prompt AI for non-stereotypical outputs by specifying regional nuances.

The concept of using AI as a tool for optimization, rather than relying solely on its generated prompts, is introduced.

The presenter concludes by encouraging continuous learning and adaptation in the ever-evolving field of AI prompting.

Transcripts

hi my name is Bob alink and this is a

recording from the presentation I gave

at AI

5050 few weeks ago in

Brussels view differently New

Perspectives does AI turn the world

upside down I have already started now

you there is also a reason why I'm

standing upside down because if I AI

turns the world upside down I have to

look at it upside down which very little

people are doing and that's what this

presentation is

about PT engineering to me in

2024 it looks like

1924 where we wanted to extract

information out of people we want to

enforce them our will and that's how

most people

prompt we determine or we say we want

this and we just want the

AI to listen to us we want it to obey

that's how we prompt engineer in

2024 and all of you no cheat sheets no

yapping offer money my life depends on

this I use it as toilet paper to me it's

worthless

crap

it's shortcuts which don't work

assumptions

and the best toilet paper to me is the

ones which claim 10 times better

performance to me this is like a 10

layer toilet people it's very soft on my

well you know

what another thing most people are using

you are now act as you are now a

copywriter with 10 years experience and

blah blah blah blah blah you're a

marketeer and again putting the model in

roles is putting the model in a template

but you have no clue what the template

is about again you assume

this and what I like most is what I call

impressive prompts when you read the

prompts and the models the roles they

are so impressive that as a human you

might think well this should give an

incredible result copyr with 10 years

experience and also marketeer your SEO

expert and 10 rolls in one uh all better

than the other ones uh it's you

don't know what a role does no one knows

but you can ask that's what I will tell

you later in this

presentation the same applies to

Frameworks we use

Frameworks and I'm not against

Frameworks they're very nice but before

you start building a

framework you need to know what you're

building and what materials you're

building it with again now you're using

roles you use words which you assume do

something you put them in a

framework and then you hope it'll

work framework should be something solid

like in this image of Steel you should

know what you're building with you

should know what the prompts really do

not

assume only when you master what prompts

really do you can start building

Frameworks and my opinion 99% of all the

people doing prompting have no idea what

their prompts are really

doing and what does this give average

results now average isn't bad but

average is average and what we see is

still more average average results and I

call it average

it's the new AI

average and the more you use Ai and the

more people use it in the way everyone

is using it now we will get average

results the trick is how to get out of

average and hopefully I'll can tell you

a little bit more about

that and because of this I think pumpt

engineering is dead the way we engineer

now

it's not the way forward so if you have

a phone now please look at it and turn

it into silence mode this is important

for the next

slide because

now we're going to remember pumpt

engineering so please show one

millisecond of respect to memorize pumpt

engineering but pum engineering is that

there is a better life after

death but what is this better

life pum engineering is that but there

is a better life after death and what is

this better

life let me tell you about

it the way we formed engineer now is

that so what we

start what we have to do is talk to the

model because

we use words now and we assume those

words do something it's like when you

talk to your colleague a friend

sometimes you only need to Blink a blink

of an eye or you need half a word and

that person knows what you

mean but when prompting you write down

words and you assume the AI does

something with those words you assume

what you think it does but it doesn't

always

so you have to start asking

it and how you can do that we'll come to

that later but we have to talk much more

to the AI what is doing the why how ask

questions questions questions questions

that's the only way you learn how the AI

really works with your

prompt and I call it it's I didn't make

up this word it's called prology

and if you do promy you become a

promist and of course I asked chat GPT

what is a

prologist

and the term suggests a blend of

technical knowledge like engineering and

an understanding of communication and

behavior AK psychology so

prology is a combination of prompt

engineer and a prompt psychologist

which is the best of both

worlds where does this lead to to boldly

go where no one has gone before because

that's where we are at the AI age we

assume but we really don't know what's

going on inside the

AI I hear experts making the AI models

and sometimes they don't even understand

why the model is doing what it

does so we have to start from scratch

and this reminds me when I was a little

kid my commodor

64 cassette tape and basically you had a

computer and there was no manuals you

copied software which was normal in

those days no manual you would just

start contrl a contrl b contrl Ctrl D

what does it do you have to

use logical sense

creativity to find out what does it do

no manual find it out

yourself and that's what I've been doing

the last 1 and a half years just walking

to the

model discovering things and it cost me

2,000 hours uh but it's very

interesting and what I've come up with

is what will you do

technique and what will you do will

actually ask the model what it does with

a prompt so what will you do when I ask

you to give the prompt and what is the

difference if I ask you to another

prompt do not execute the pump but

explain me what you will

do this has given me lots of insight in

what the model really does with a prompt

one of these insights

was we pumpt in English or German or I'm

Dutch uh we can pumpt in Portuguese

which I talked to someone recently

and most of you have seen that the model

sounds typical American so although we

pum in our own language the model still

sounds

American now the very simple solution

for that is tell the model which country

or region you're in and again that's

something you can ask the model what

will you do when they ask

you uh this is the region and without

region and then it will tell you you it

will go in a different mode and consider

the regional

aspects and again you can also ask it in

the roles what will you do when I ask

you to act as a copywriter to rewi the

text and what's the difference if I ask

you to act as a French Belgium

copywriter again this is an example

everyone uses roles now but before the

role you should really put the country

in front of it because putting country

in front of a role will put that role in

a more targeted uh targeted role for

your country you will notice it will get

better I will I'm again I'm not a fan of

copywriter or

marketeer uh there are different

techniques where I can control it much

deeper but if you use roles at least put

country in front of the RO it will make

the output uh a lot better and again you

can ask it here uh FR Belgium

copywriter uh what's the

difference ask it just use these

techniques it will give you more insight

in what it does now what I've also

found is it tends to get

stereotype like it gets stereotype

English it could get stereotype

Belgium again act as a non- stereotype

French Belgium

copywriter you will notice this and it's

like when you read the text you analyze

it you see well this is like stereotype

what you think put it in a prompt it's

as almost as simple as that and again

you can ask it ask it ask what you have

in your head ask it and compare it to

the prompt you were using

again this will give you Insight in what

the model does at least that's what I've

been doing the last nine months and it's

gotten me deeper and deeper in the

model understanding what it does is it

always right

no but n out of 10 it

is so copywriter General Improvement of

quality now if I took the French Belgium

copywriter it says faing the text to

French Belgium

speaking cultural and linguistic Norms

the non-stereotypical French Belgium

copywriter ensuring the Texas culturally

sensitive avoiding cliches and providing

a modern respectful portrayal of the

audience this is the summary of the

previous prompt I asked the model to

compare the three different

prompts it's as simple as that so if you

use non-stereo typical French Belgium

copywriter or

put Portuguese uh I talked with recently

talked to someone from Portugal and he

said well when I use Portuguese it

sounds uh almost Brazilian which in

Brazil they're using also Portuguese

turns out if you ask the model about

Portuguese it uses International

Portuguese so you really have to tell it

use Portuguese Portuguese targeted to

Portugal it sounds almost

ridiculous but this is how the model

works

what will you do

technique

uh I ask it

also uh generate make create or craft

curiosity Gap title now most of you like

I did in the past make this make that do

this do that generate make create or

craft all sound familiar

same but when you ask a model the

difference is it gets very

interesting when I use generate focuses

on a systematic perhaps more formulaic

approach make implies a bit more

customization based on provided details

create suggest a more original and

inventive process and craft emphasizes

precision and careful construction for

maximum effect so the next time you

are going to make a title or curiosity

Gap try craft or create you will find

that when you use craft a title the

model will use different parameters and

it will get a better you will get a

better result same for create now when

you make a Excel table for example you

could say generate make create or craft

it will won't make a difference again

you you can ask

it ask it when I make a table when I use

generate make Creator craft is there any

difference no because a table an Excel

table is an Excel table and it doesn't

make a difference but creating a text

crafting a text a title that makes a

difference again these are just four

words there are many more words which

you could use and ask about it so this

is what I mean with

you think you prompt something but you

have no idea what the model really does

and only by asking you can find out what

the model does with the words you're

using how does the model really use

those words in what mode will it use it

and again this will bring you

further and it will get you away from

average because aage that's what I see

in the new

models uh I have to

use deeper and deeper prompting to get

out of

aage people say the model gets better

yes it does for the average user using

less pumps it knows what you

mean but it will give you average result

based on what it learned from all the

people and it's taken the average

sponsors from those so yes for most

people it will get better but it will

get average and I call it

average what you really want is more

colorful you want to get away from the

average result as an expert in marketing

or copywriting or anything else in your

field you want to get away from the

average result you want more you want

better you want more colorful now here

we have some colors of green so if you

go and promp deeper you you will get

some nice shades of green there's a

little bit of blue but what you really

want colors you want all the colors you

want generative

Ai and generative AI is really

using the

model at its best it's combining things

which have never been combined

before uh an

example yenga block game yenga is is a

game now I tried a couple of months ago

or half a year ago use yanga as a

summary yenga is not a summary

technique and I asked the model well

what will you do when I use yenga as a

summary I don't know yenga summary

technique and I had to told well use

yenga like the block game as a summary

technique and then it starts a

generative approach

yenga is taking out

blocks and it says well I have to take

out pieces of text similar to

yenga until I have all the important

pieces of text it's a completely

different summary technique and that's a

good example of generative

Ai and when you use generative

AI your human creativity you can do the

most incredible creative things but in

the end it's all about your

creativity your creativity makes

generative AI possible the AI model

itself knows a lot but in the end it

doesn't know what it knows it only knows

what's combined in this data set so if I

combine like yenga and

sumary it's never been combined

before and that's generative AI so your

creativity this makes generative a i

possible and it will make it possible

that you outgrow the average the average

results a very nice example of that is

low literacy FSE friends

Nigeria I started with this on a project

a couple of months ago write a text for

low literacy which is a common problem

in the Netherlands and in many many

countries false friends I'd never heard

about it

but it's interesting because I ask you

well what will you do when I ask you to

write a text in low literacy and the

person I'm writing it for comes from

Nigeria then it came up with false

friends and false friends are basically

words in English which have a completely

different meaning in Nigerian or take

any other country so what you could do

is rewrite this

text for someone who has low literacy

is originally from

Nigeria and prevent false friends so

what it will do then is it will rewrite

this text in English or any other

language and it will substitute the

words false friend words for other words

so that people in this case from Nigeria

will not get confused now this is a very

nice example of generative

AI you need to be english- speaking and

from Nigeria to know these

words otherwise you would have no clue

about this so for me this is an eye

opener and again you can ask the model

about it what will it do uh is just

combining things which it already knows

it knows low literacy it knows false

friends and now you're going to combine

it it will not do it by itself unless

you tell it to and that's your strengths

as a

prologist your creativity you can do do

amazing things like this the courses for

this which you can follow TH th000 or

more and at the Press of a button using

a prompt you can use

this so again you can ask it what will

you do if when I ask you to rewi a text

for someone with low literacy in Belgium

was originally from Nigeria and prevent

the use of false friends explain what

you will do and now the model will

explain you what it will do

asking it's the only thing I do ask ask

compare only by asking and comparing you

will see the differences between small

words one word difference can make a

huge

difference compare ask and this is how I

learn and this is I think how you can

learn mastering the AI and get the best

results out of it yes it takes time it

takes a lot of time shitload of

time so there's no shortcut there's no

cheat sheets you have to

learn I can tell you now so you you can

learn from this and this will save you a

lot of time uh but in the end uh you

will have to master it and that takes

time another example marketing

psychology if you're into marketing F

Alini Pock caraman burgler David Rock

scar prevent reactants this is what I've

been using in my profiles that I built

and these are

all psychological marketing Frameworks

cini has seven principles he's the

world's best known influence specialist

BJ ful has a different system canaman

system one and two which says as a human

you look at things emotional which is

system one and rational you look at

technical specifications system two

berglar the dialogue method David Ro

scarf something completely different

again you can ask the model what is

David walk scarf model explain it to

me

these psychologists have never been

combined and the AI model knows them and

I can combine them that's again

generative AI you can combine all these

different psychological models but be

careful not all of these models can be

combined so you can again you can ask it

this is my

purpose this is my target audience I

have these and these psychological

principles uh can I combine

them and the model will tell you yes or

no I have used some psychological

systems and it would just say no it's

it's the opposite effect or it just

doesn't work you only know when you ask

the mother

and again it will give a pretty good

result uh when you ask

it nice example I heard about story

brand framework never heard of it before

it's like I I hear about things I never

heard before so the only thing I do is I

start asking the model what a story

brand framework and can I combine this

with this case the David Rock scarf

model which works very nice for human

resource for certain uh certain jobs

combination David Rock and story brand

is a killer not fall but again you can

ask

it again you hear you see different

things can I combine them now these are

Frameworks

from

marketing uh out of the box thinking is

really use the yenga technique or

summary which yenga and summary is

completely different so if you really

want to go out of the box uh use a

technique

from completely different market and use

it in your market

and combine it but ask it what it will

do only when asking it what it will do

you will know whether it works or not

give your purpose give your target

audience then you give the different

models Frameworks you want to use and

ask it can I combine this and what will

it

do you will get amazing results this way

but only when you ask it you will it

will tell you whether it works or

not it it might work because in the end

the AI just makes assumptions based on

what it

knows and sometimes it's completely

wrong they can be combined or the other

way around but nine out of

10 it's right so again it will make you

more creative if you're creative it will

make you more creative and you can do

things a lot

faster and one of the things I've used

in the past is the power of three words

in a row which many of you see in

marketing if you're marketing you will

know a fun restor effect which is

basically when I say I see a table a

chair a

lizard table now lizard doesn't fit into

this which is a from westof effect which

you will see on many web pages where you

see most salt it's it's highlighted now

you can do it subtle or you can do it

not

subtle in this case I ask it use the

power of three words and also one of

these three words should be a cini

principle reciate reciprocity in this

case so when I have fast free

fresh the word free fre is the from

Resto effect word you will you will see

free free is also C principle so in this

case I use the power of three words all

starting with an

F from west of effect and a c principle

now in my book I wrote I have an example

of this is a uh

solid exclusive stylish

chair now when you use exclusive for a

high price product the word exclusive is

what you read when I use this is a solid

safe stylish chair and you sell

children's chairs the word safe is

something which you want to read as a

parent again that's a from of effect and

you can use this use the power of three

words in a row a from of Effect one of C

line principles and instead of the word

free give me 10 different

words when you ask for 10 different

words there's always a word in there

which will fit in if it doesn't ask for

10 more for 10 more this will make it

very simple to do subtle psychology

using these different techniques which

have again never been combined before

and that's the the

strengths of generative AI I mean I

really like it

I'm I can't get enough of

it and practical examples of what what

I've been doing with this is uh creating

friend voice style

profiles and I use up to 80 elements so

most people think about tone of

voice but there's also tone there's

voice there's style there's language use

and these are just five elements which I

use when I create brand voice and style

profiles I also add marketing to that

but what I've been doing the last nine

months is creating

profiles where I can control the output

of any text so I can create a

journalistic profile and can create a

apple like profile uh I write like Ikea

add marketing to it I can use famous

bloggers uh let them sell products by

adding marketing to it again I'm using

what you saw in the previous spreadsheet

cini for caran fogler scarf model and

reactants uh this has taken me a lot of

time but I'm now able to control almost

any text the way I

want uh 80 elements is a

lot uh but this is really how I can

control the AI when people say right as

a copywriter or a

marketeer I think it's nice but it's

beginner because you don't know what

you're doing what I'm doing with these

profiles the ad elements is really

controlling how should this copyright or

right what language what style what tone

of voice plus up to 80 elements

including marketing so I'm not saying

it's a marketeer really specifying what

it should do it's me making the template

what it should do and this is really how

we should start using AI is controlling

everything uh but it's difficult the

deeper you go the more difficult it gets

and as I said this has taken me hundreds

of hours uh of time to understand this

uh lots of

frustration uh but it's it's working now

and uh it's a very nice example of

generative Ai and I was only able to do

this by asking the

model but we have Evolution and

evolution is very nice because uh once

you've mastered your prompting and you

think you understand how the model

interprets your

language we get the next model so we

have Chad GPT 3 and a half we have four

we have 4.0 five is around the corner we

have Claude we have

Gemini and it evolves and it means that

the words you were using half a year ago

the

prompts they might not work on the new

model or they might not do what you have

been doing and that's what I've seen in

Chad

GPT it gets better when using simple

prompting but again this gives the

average

results and to get out of that average

result I have to prompt even deeper I

have to tell it what it can do and what

it can't do and that's sometimes very

frustrating because you had a prompt

which worked very well but the more the

model develops the more it will make

assumptions based on what the average

user

wants and this means that probably next

year it will do a very good job for the

average

user but for the professional user who

wants to get out of that average result

you really have to understand what it

does using that prompt and then you have

to start negative prompting you can't do

this you can't do that you have to do

you have to do it this way you have to

do it that way and that means you have

to keep on prompting keep on asking what

it will

do and this will take a very long time

and as AI

evolves it means you have to go deeper

deeper and deeper into the model uh to

control it

and yes that you need creative thinking

for that logical thinking analytical

thinking and again lots of time now some

of these things can be automated because

we see agents now and I like the idea of

agents and you have agents talking to

each other I see people using uh AI to

make their

prompting again it's nice you can have

ai do your prompting but the AI can only

prompt it knows in its data set in the

previous

examples previous slides I gave you an

example of things I combined the AI

could never combine those because it

doesn't know how to combine them so yes

what I'm doing now

is I make my own

prompts combining things which have

never been combined before and then put

them in the AI to optimize my prompting

but yes I have the AI help me but I

still

first I make my own prompts and then

have ai optimize it and that's how it

will work for a long time if you want to

get away from the average

results so I hope you liked my

presentation if you have any questions

you can follow me on

LinkedIn send me an email and thank you

for your time and Happy prompting

everyone