---
type: raw-transcript
title: "3 MOST Important Prompt Engineering Techniques you NEED to know!"
youtube_id: yo5liQr6Wy4
url: https://www.youtube.com/watch?v=yo5liQr6Wy4
slug: 3-most-important-prompt-engineering-techniques-you-need-to-know
published: 2023-05-28
duration: "0:10:46"
fetched_at: 2026-07-21
immutable: true
---

## Transcript

**[0:00:00]** one of the biggest buzzwords going around in the AI space right now is prompt engineering all prompt engineering is is crafting your questions to the AI in a way to get the answer that you want so if you're bad at prompt engineering you're going to get bad answers from the AI if you're good

**[0:00:17]** at prompt engineering you're going to get great answers from the AI and there are two types of people in this world right now there are people who don't know enough about prompt engineering and so when they use chat GPT or other AI models they can often be disappointed

**[0:00:31]** with the results they get but really it's because they didn't ask the questions in the right way and the other kind of person which I'm sure is a lot of you watching this video right now you are way too into prompt engineering and you've done research on the dozens and

**[0:00:45]** dozens of different techniques and methods for prompt engineering to get the exact answer that you want and it can be kind of overwhelming because you have all these different ideas going through your head how you have to craft the perfect prompt and that just makes it take longer to actually write that

**[0:00:59]** prompt and get the answer from the AI when really something simpler would suffice and it would be just as good the output from the AI model would be just as good and so what I want to talk about today is the three most important prompt engineering techniques and I also want

**[0:01:16]** to talk a little bit about what goes into more custom prompt engineering for specific tasks and talk about why there are some things that you really don't need to worry about with prompt engineering because it's important to keep it simple as well alright so I want to keep this nice and short the first

**[0:01:32]** prompt technique is to have the AI criticize itself very simple I'll show an example here and then we'll move on so the first one is write a tweet about building a personal brand and so it writes a tweet right here but as you can see this tweet is lame it's very generic

**[0:01:49]** it doesn't actually provide any wisdom it's not engaging or insightful in any way and so all I need to do to get a better tweet is to personify the AI that you are a Critic who specializes in critiquing tweets and also I give it a couple of requirements like you make

**[0:02:07]** tweets engaging you make it so they aren't cheesy that's a really important thing because a lot of times when the AI is given creative tasks it can be easy and then I also give a couple of very specific requirements like you don't like hashtags and you don't like tweets

**[0:02:21]** that don't actually provide any value and then also you want tweets to be specific and not General so I take my idea of what makes a good tweet and I just be really specific with the AI and tell it to critique itself very simple and so then I just tell it to critique

**[0:02:36]** the tweet that it just made and then write a better tweet based off of its feedback and observation and it gives me really good critique of its own tweet and then sure enough it gives a revised tweet that is actually pretty good if I was making a Twitter account tweeting

**[0:02:51]** about creating a personal brand I might post this it's good like it's not super great there's definitely something that can be said for human insight and into solving their own problems and sharing this with the world but this is genuinely good advice and so that's the first one the first concept around

**[0:03:08]** prompt engineering which is to have the AI critique itself and so now moving on to the second idea I've got for you guys here and again this is for people that are new to prompt engineering or people that have done way too much research into this the second example I have

**[0:03:22]** highlights the issue with AI oftentimes just when you ask it for an opinion on something or the better way to do something or what you should do it'll just say it's subjective and it'll still give a good answer but it doesn't give you the exact answer to the question

**[0:03:38]** that you're asking an example I have right here is I ask should I wrap my car with blue or purple I'm going for a sporty and summertime look now if I didn't include this first sentence it really would be just a subjective thing there's so many factors that could go

**[0:03:51]** into what's the best color for a car but giving it this bit of context like there's something to work off of to really give an opinion however the AI says that it's subjective and it doesn't give a good answer for exactly what I'm looking for now what it spits out here

**[0:04:08]** is pretty cool like it's really insightful and it talks a lot about what might make me decide blue versus purple for my car color but a lot of times when you're asking an AI question you just want an answer fast and you want to be a direct answer you want the opinion of

**[0:04:22]** the AI based off of what information whatever information you decide to give it and so what I do here is I say you're a car designer specialist who freely gives their opinion no matter what even if the question has a subjective answer and so then I just asked the question

**[0:04:40]** again and so just like the last example I am personifying the AI I'm telling it to fulfill some role to help me which is the biggest overall important concept wrapping around all of prompt engineering because you want to personify the AI to be some sort of role and so then when I ask it the question

**[0:04:58]** again it says in that case I recommend wrapping your car in blue there we go that's exactly what I want I want a direct answer to quickly get to the point and it also justifies it in detail as to why it recommends blue and then it says at the end that it's subjective so

**[0:05:14]** it goes back to that because really this is subjective so I appreciate that it still recognizes it yet it gives me the answer that I'm looking for it gives me its opinion so that is number two number three a lot of times when you are asking the AI a question you want a specific

**[0:05:30]** response format especially when you're working with the API for something like GPT and you need the AI to return something in a specific format or your program won't be able to understand that response and it's actually fairly easy to get exactly what you're looking for so for example I asked it the answer to

**[0:05:51]** this math equation and it gives me some background on what it does to make the calculation and then it actually makes the calculation giving me me the correct answer of 140 and this is cool and all but if I have an application that is doing math by interacting with GPT for

**[0:06:09]** whatever reason and I need to understand the answer from GPT and I need the format to be the same every single time this won't cut it because the AI might decide to answer it differently where maybe the last word in the response is not the answer or maybe there's not a

**[0:06:26]** period here there's a lot of different ways that this could go wrong where my program would break because it expects it to be in a certain way but you can force it to respond in exactly the way that you want and the way that you do that is by providing examples question

**[0:06:39]** and answer and then you ask it the question and say to follow the answer format that you gave in the examples and so I have my same math equation right here and I say the answer is 140 and then I repeat the process and then I ask a third question and I tell it to give

**[0:06:54]** my answer in the same format as the other answers and sure enough it gives a colon 5. and so within an application that does math equations with gbt I can actually have it expect the answer to be an a colon and then answer and I could parse it in that way every single time

**[0:07:10]** in the AI without fail will do exactly what you tell it here and so the idea here is to give examples when you need a specific format and giving examples can also be very powerful when it doesn't quite answer the question in the kind of voice or tone that you're looking for so

**[0:07:28]** a lot of times with creative content like when you're asking the AI to help you write tweets it can be too cheesy or it doesn't really match your own voice you need to give it examples for it to actually understand this is how this person talks and so when it asks when

**[0:07:44]** this person asks me for tweets I need to use this kind of language or this kind of grammar to match the examples they are giving me and so that's another powerful example of how giving examples before you ask your question that AI can be super useful and another thing that I

**[0:08:00]** I wanted to point out here I've kind of covered my main three points here I want to talk about some prompting techniques that a lot of people recommend that aren't actually useful the first one a lot of times people tell you that you need to tell the AI to think through

**[0:08:14]** their answer step by step now that can be powerful if you're working with a less powerful AI model but with something like gbt4 it already does that really well in fact when I Was preparing for this video I asked this mathematical question and it literally started the response with let's think this through

**[0:08:31]** step by step so it already knows to do that you don't have to waste your time experimenting and researching all these different prompt engineering techniques when a lot of them don't actually make the answer better you have to keep that in mind sometimes people will show you here's a prompt that I've created and

**[0:08:47]** you want to follow this format to get the answer but really it's only working well for them on a couple specific examples they show you but in general it's not going to make the answer better and therefore you just wasted your time on your research and actually implementing that technique in your

**[0:09:02]** prompt engineering and so that's a big one is telling it to Think Through step by step and there are a couple of other examples that maybe I'd actually make a separate video on just to show some ways that you could save time by just thinking about or not thinking about

**[0:09:17]** rather some other prompt engineering techniques that aren't as useful but I think I'll keep it there just to keep this video rather short and so yeah I think that kind of wraps it up in general I wanted to make this video for you guys so that you know how to do

**[0:09:32]** prompt engineering well and not waste your time with crappy prompt engineering that doesn't actually make your answers better so again to summarize the first one is you always want to ask the AI to critique itself when it doesn't quite give you the answer that you want because it'll always give you something

**[0:09:47]** better the second one is when it's telling you that an answer is subjective but you just want its opinion based off what you give it always tell it that you are the kind of person that gives their pain no matter what and go from there and then the third one is when you need

**[0:10:02]** a specific format or you want it to give an answer based off of examples that you want to provide always give examples in the prompt and then ask the question after and those examples are often question and answer format so you give a question an answer to your own question

**[0:10:17]** a question an answer to your own question and then maybe repeat that a few more times and then you ask the question and say give me the answer in the same format really powerful techniques that you can use for really any kind of prompt any kind of question

**[0:10:30]** you have for the AI and it will make it better so thank you everybody for watching if you found this insightful remember to like And subscribe to this channel it really helps me out as I'm growing through this AI content Journey but yeah thank you everybody for watching and I'll see you in the next

**[0:10:44]** one
