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This one prompt makes GPT-5 INSANE
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Chad GPT5 is the best AI model ever
released. The issue is if you don't
prompt it correctly, your results are
going to be horrible. After using GPT5
non-stop since it came out, I've come up
with a prompting system that will make
your results 10 times better. I'm
telling you, if you steal the prompt I'm
about to show you, you'll be oneshotting
things with AI you never thought
possible. Let's get into it. So, I came
up with this master GPT5 prompt. I'm
going to show you in this video. We'll
go through all five stages of this
prompt. So, there's five parts of it.
You'll be able to copy and paste it and
use it however you want, but I'm going
to walk you through each one of these
five stages in the prompt. I'll unlur
for you step by step. Last week, after a
lot of complaining about GPT5, Open AI
released an entire cookbook of how to
use it. This is what that cookbook
looked like. And it's this huge guide on
exactly how GPT5 works and how you
should be talking to it. So, I basically
went through all of this and I went in
and I created a master prompt based on
the recommendations that OpenAI gave.
This basically takes hours of advice
OpenAI came up with and puts it into one
simple prompt. You can copy and paste,
fill in the template, and you're going
to start getting incredible results.
It's really critical you stick through
this and learn the entire prompt because
this is going to be the only way you get
really good results out of GPT5.
Unfortunately, GPT5 isn't that good if
you're not prompting it correctly, which
I understand people don't like. But if
you do use it correctly and you use this
prompt I'm about to give you, the
results you're going to get are way
better than any other model you can use.
So, let's get straight into it. Let's
get into the master prompt. The first
thing you want to give GPT5 when
prompting it is the role it's taking.
Right? Just straight up the role. Very
simple, one sentence. What role is GBT5?
The reason why roll is so important in
the prompt is GPT5 only does exactly
what you tell it to do. Nothing more,
nothing less. So, if you want it to do
something really well, you need to give
it a very specific role. So, the example
I'm going to be showing you throughout
this video is we're going to be building
a master prompt for planning and
building out an application. This is
going to be an application for YouTube
creators. It helps them plan videos and
make scripts. And so I'm going to build
out an entire prompt for but first
giving the role you were a product full
stack app planner for indie creators. So
for you depending on what you're doing
right you'd make your role you know
you're a product full stack app planner
for video games or whatever you want or
you're a master researcher for trending
news items whatever that task is you
want to do you have to think about the
perfect role for the AI. So the first
line in our master prompt is going to be
that role, right? We want to make sure
right away, right off the rip, before
GPT5 goes into anything else, it knows
what its role is. So here's where things
start to get interesting going into the
second part of the master prompt, we
have a control panel. And so if you read
through OpenAI's cookbook for GBT5, one
of the biggest parts here is the amount
of options they give you. They talk
about making control the verbosity of
the model. They talk about controlling
the amount of thinking the model does.
There are a whole bunch of factors that
on the negative side GPT5 isn't
fantastic at figuring out on its own.
Out on the positive side, it's fantastic
if you control those parameters and tell
it how much to think and how verbose it
should be. So, going back into the
master prompt here, you want to put a
control panel with all your first main
prompts, right? You want to control
reasoning, verboseity, the tools it
uses, for it to self-reflect, for it to
metaphix, and I'll go into what those
two mean in a second. But you want to
have when you build your kind of first
master prompt, when you're taking on a
major task, to have this control panel
where you control all of these
variables. So, going back into our
prompt we're building here, I put in the
control panel. For this use case, I'm
going to have it do ultra think, so
think as hard as possible for this
prompt and planning out this app. I'm
going to have the verbosity be medium,
so it's not a ton of extra information.
I want to have it use most of its tools,
so web, code, PDF, and images. I want it
to have self-reflection on, and I wanted
to have metapixing on. So, real quick,
you can probably figure out what these
three mean. And for a full list of
tools, I'll include that down below as
well for what tools GPT5 can use. But
what does self-reflect and metaphix
mean? These are two very important
features of GPT5 that actually makes it
very very powerful. Self-reflection is
basically GPT5's ability to when it's
about to execute on a prompt, it'll
actually reflect on what it's doing in
that prompt and improve the prompt
before it executes. Right? So, if you
give it a prompt, it's about to execute
on it, it will actually self-reflect on
that prompt and figure out ways to
improve it before it actually does the
tasks in the prompt. And this is a
really powerful feature in GPT5 you need
to be taking advantage of. This is how
you get really really good results. And
then there's also metaphix. This is
another really powerful feature. And
again, these are all things talked about
in here in the GPT5 cookbook. Metaphix
is actually its ability to reflect after
it executes. So self-reflect reflects
before it executes. Metaphix reflects
after it executes. And so after it
executes on your prompt, it'll actually
go back, look at the results, and
improve the results if the results
didn't match exactly what you were
looking for, right? And so these two you
want to have on most of the time. As
long as you have time to spare waiting
for the answer, you want to have these
on. If you're in a rush and timeliness
and quickness of the model is important,
you'll go ahead and you can turn these
off. And I'll go at towards the end of
the video into a lot more detail on how
these two work because there's more to
this prompt that actually ties into
these two options. But basically what
you want to do here is with every one of
your first prompts you do, right? You
want to have this control panel and you
want to control these different
variables in GPT5, right? So for
reasoning, you can do think, think hard
or ultra think. For verbosi, you can do
low, medium, and high. And for tools,
here are your different options. If you
don't want to choose specific tools, you
can just use auto. But getting into the
granularity of controlling each one of
these variables is going to give you way
way way better results with GPT V. I'm
not kidding. If you do these things,
your results are going to be amazing.
Equally as important as this control
panel is what we are going to go into
next in this master prompt. So the next
part of the master prompt is a really
simple task. So usually what people do
when prompting GPT5 is they actually do
only step three and none of the other
things. They usually just give it a
task. So this step three is probably the
one you're most familiar with, which is
giving the model a really simple one-s
sentence task. The reason why you don't
need to go into super detail here is the
rest of your prompt is going into the
important detail. This is just simply
what you want the model to do. So for
this example, when it comes to building
and planning the app, we're going to say
plan and scaffold a minimal app called
YouTube topic scout that finds trending
ideas, scores them, and generates a
script outline. And so basically we're
building like a YouTube planner and
scriptor for us. And so the task very
simple just planned and scaffold out
this minimal app and we gave a short
description what we want this app to do.
We don't need to go into a ton of detail
here because the rest of our master
prompt goes into all the other details
we need. So again just the task just
exactly what we want the model to do and
nothing else. So next, the fourth and
second to last part of this master
prompt that you really need to learn to
get incredible results from GPT5 is
going to be inputs. Right? So this is
probably the only optional part of the
prompt. Right? If you haven't done much
planning or thinking about what you
want, you don't need to put this inputs,
but if you have context you want to put
in, this is very important. Basically,
what inputs are is important context you
want to give GPT5. This is basically
going to be a list of notes, of links,
of other data, of other thoughts, of
other ideas, of comparisons, things like
that. I'll show you a couple examples in
a second here. But this is important
context you want to give to the model
before it does its execution for the
task you're asking for. So, for example,
for building out this app that we're
planning here, I'm putting in the user.
So, who I think's going to be using this
app, the core loop, what I want the
experience of the app to be, different
information about how I want them to
score the inputs of the app and score
what the topics are that they're
planning in the app, non-negotiables,
tech preferences, tone. So, I'm just
giving as much context of things I
already thought about for this app that
I wanted to build. Again, this is
completely optional, but you want to be
brain dumping in as much context as
possible. If you're building out or
planning an app, you just want to put in
all the different ideas you have for the
app already. And this is going to be
really important context. Maybe if
you're having the AI build you content,
what you would put in here is other
comparable content or other comparable
content creators, you want the content
to sound like, right? This is going to
be all the context that's important for
this prompt we're building for GPT5. As
you can see, our master prompt here is
looking pretty good. We're giving it a
lot of information so far. At this
point, it's already probably giving you
way better results than any other
prompting you've been doing with GPT5.
But let's go to the final part or the
final part of the master prompt for
GPT5. So, the fifth part I want to show
you in this mass prompt, this is
actually not the last part. I have one
more thing I want to show you after this
that's important to include in the
prompt. So, stick around for that. But
the fifth part that you actually want to
customize in this prompt is the
deliverable. So, this is a list of
precisely what you want in return from
GPT5. what you want it to actually
output to you after it does all its
self-reflection. So here's what it looks
like for us in our example of what we're
building here is when we're planning out
this app. We wanted to give us a PRD, so
a product requirements document. We want
to give it a competitor scan. So we
wanted to go research all our
competitors for this app. We wanted to
give us an architecture, an API spec,
what the UI looks like, starter code. So
this is actually a really complex list
of deliverables. And if we didn't
include these deliverables, GBT5
probably wouldn't output this. But
here's the thing. GPT5 is so powerful
that it can actually handle doing all of
these things in one shot. Because we're
using this master prompt to get the
output from GPT5, it'll actually be able
to get us all of these deliverables,
right? Because we also included what
tools we wanted to use, the amount of
reasoning we want to use. because we
included those options, it'll be able to
oneshot a lot of really complex things.
And so what you want after your inputs,
after your context, is the deliverables
of what you actually want out of this,
the results you want to get from the
model. And because we're doing all
these, again, fine-tuning using specific
variables, we're going to be able to get
not only all these deliverables, but
also all these deliverables done really,
really well. But these deliverables are
only high quality if you include this
last part in your prompt, which is going
to be this little private ops part here.
So, this is down below as well. I'll
have this entire example prompt down
below, but private ops is basically
describing to GPT5 how the self-reflect
and metaphix works. In the cookbook that
Open AI put out, they had things like
how to score itself when it's
self-reflecting, right? had talked about
how you should be using a self-scoring
rubric. And basically what that means is
when GPT5 reflects on the prompt and
reflects on its output, it should score
its output from like 1 to 7 and then
improve the output based on that rubric
scoring. Right? This is how the GBT5
model was built. And now what we're
doing is we're basically going in and
we're defining that for the model. We're
saying this is how you self-reflect.
This is how you metapix. This is how you
build the rubric for yourself.
Self-reflect and metaphix so that you
get even better results. Now, I know
what you're thinking. I got this comment
on my last GPT5 video, which is why the
heck do we need to do all these things?
If this was a good model, we shouldn't
have to control the verbosity and the
reasoning and all this. And you know
what? I agree with you. I agree. You
shouldn't have to do these things. And I
think in the future, you're not going to
have to do these things. I think in the
future as the model evolves and we get
GPT6, you're not going to have to
control all of these things, it's going
to be able to kind of figure it out on
its own. But at the moment, you have to
control these things. And in my opinion,
it is very much worth it because here,
I'll show you. I'll hit enter on this
and we'll start running this prompt. At
the moment, GPT5 from a raw power
perspective, just raw power of what it
can accomplish is the best. It is the
best model out there from a raw power
perspective. The outputs you get, the
things it can accomplish in one shot. It
is completely unmatched. So, yes, do you
have to do a lot of work to get good
results? Yes, you do. Would I rather it
so you don't have to do all this work?
Right. I would rather not have to do a
lot of work. You're 100% correct about
that. But here's the thing. If you put
in the work, you're going to get
exponentially better results, which I'll
show you in a second here as it thinks
through this, your results are going to
be way better. So, it's up to you. Do
you want quick results? That's fine. You
can use GBT5 like you were before. But
if you want great results, you want to
be controlling all these different
variables. And here's the thing, you
don't need to do this entire prompt
every single time you prompt GPT5.
That'd be ridiculous. If you had to do
that, I wouldn't be using GPT5, right?
But if you're starting a new
conversation, you're starting to go down
on a very important path, like you're
building out a new app like we're doing
here, right? This first prompt, you want
to have all these variables and options.
The first prompt, you have all this
control that puts it's almost like the
planning mode in clawed code in a way
where it's like the plan controls
everything else and everything else can
you can do really quick. Once you got
this really good strong first prompt in,
you get your first results. From there,
you can iterate very quickly. You don't
need to use this master prompt every
single time. But if you're going down a
path where you're doing something really
complex, like building out an app, that
first prompt you want to use, you want
to use this master prompt. And you're
going to see why in a second once it
outputs all this information. Okay, so
it's all done. It took 2 minutes and 21
seconds. Let's see what GPT5 came up
here. It first it has the initial code.
Okay, so it wrote all the code for the
app. So we'll be able to take that code
and we'll have V1 of the app. It also
has C data in there. So you can run this
and it'll have C data. But let's see
what else we got here. We have the PRD
markdown. Oh, and it had a metaphix
applied. So apparently it built the
product requirements doc and then went
back and fixed it to make it better
because it didn't match the scoring on
the rubric. So here's the product
requirements doc. It has a goal. Primary
users, jobs to be done, MVP, what should
be in the MVP, nice to have, success
metrics, non-negotiables. Okay, so it
has a competitor scan. So, it searched
the web and found four competitors. I
actually use Vid IQ quite a bit. It's a
pretty good app. Uh, so this is real.
This is true. These are true competitors
architecture. So, it has the entire
architecture. It has the schema for the
database. It has the API spec, so how
you would plug in the API to get data
for the app. It even has wireframes. So,
let's let's take a look at the
wireframes. We'll open this up. Here's
the wireframe. So, you can see what the
kind of homepage, a little mockup of
what the homepage would look like. Let's
just check out what the uh the other
ones look like here. I'll download this.
It'll show you some other result cards
for the different topics it comes up
with. So, it makes the PNGs. So, we're
making PDFs, PNGs. We're writing code.
And then it even has an entire zip file
for all the code that we can scaffold
the app out with and an explanation of
what's inside that zip. So, did what we
asked for. That's pretty incredible. All
in one shot. Now, from here on out, I
can prompt it just as you normally would
any other model. We don't need to use
that huge big prompt every single time.
Now, it already has enough context where
we can just go back and forth now and
tinker with what we have here. Using
this master prompt is going to get you
so much better results with GPT5. I
promise you, if you use that prompt I
just showed you, you're going to get the
best results you ever got out of an AI
model. If you learned anything at all,
make sure to hit subscribe. Make sure to
join the free vibe coding community I
built, link down below. Only free vibe
coding community on the internet. I
promise you'll learn a ton. You'll love
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