Automate ANY task using ChatGPT! (with GPT actions feature)
Summary
TLDRThis video tutorial offers a comprehensive guide on automating tasks using AI, specifically within a chat GPT interface. The host demonstrates how to integrate various applications like WordPress, Google Docs, and social media platforms to streamline workflow. By leveraging GET and POST requests, viewers can retrieve and send information efficiently without leaving the chat. The video also introduces 'schema ninja,' a GPT designed to assist with complex automation setups, promising to save hours of manual work. The presenter emphasizes the importance of understanding AI foundations for personal and professional productivity, inviting viewers to join a community for further learning and resources.
Takeaways
- π Chat GPT can automate tasks efficiently if used correctly, avoiding the common mistake of copying and pasting between different platforms.
- π The video demonstrates how to integrate Chat GPT with various applications like WordPress, Google Docs, Google Sheets, and social media to streamline workflow.
- π Staying within Chat GPT, users can retrieve and send information without leaving the interface, enhancing productivity.
- π The presenter provides a step-by-step checklist and resources to guide viewers through automating tasks within Chat GPT.
- π‘ Understanding the underlying workings and terminology of Chat GPT, such as GET and POST requests, is crucial for effective automation.
- π GET requests are used to fetch information from external sources, while POST requests are for sending or updating information on other platforms.
- π οΈ The video introduces 'schema ninja', a custom Chat GPT designed to assist in creating webhooks and automating processes.
- π The AI Foundations Community is mentioned as a resource for learning to leverage AI for increased efficiency in personal and work life.
- π The process of creating a Chat GPT, including naming, description, profile picture, instructions, and conversation starters, is outlined.
- π A detailed walkthrough of setting up a webhook, creating an automation in make.com, and connecting it to Chat GPT is provided.
Q & A
What is the main focus of the video?
-The main focus of the video is to demonstrate how to automate tasks within chat GPT by integrating it with various applications like WordPress, Google Docs, Google Sheets, social media, and emails.
What are the two types of requests mentioned in the script?
-The two types of requests mentioned are GET and POST. GET requests are used to retrieve information from external sources, while POST requests are used to send or post information to other sources.
How can one stay within GPT to automate tasks?
-One can stay within GPT to automate tasks by setting up webhooks and creating automations that connect to various applications, allowing for the retrieval and sending of information without leaving the GPT interface.
What is the purpose of the AI Foundations Community mentioned in the script?
-The AI Foundations Community is created to help individuals become more efficient and productive by teaching them how to leverage AI in their personal and work tasks.
What is a webhook and how does it relate to the automation process?
-A webhook is a user-defined HTTP callback that provides a way for an app to send data to another app in real-time. In the context of the script, webhooks are used to trigger automations and facilitate the flow of information between GPT and other applications.
What is the role of the 'schema ninja' in the automation process described?
-The 'schema ninja' is a custom GPT designed to guide users through creating webhooks and setting up automations. It provides step-by-step instructions and helps in generating the necessary schema for the GET and POST requests.
How does the video script guide users to create a GPT with specific functionalities?
-The script guides users to create a GPT with specific functionalities by outlining the steps to name, describe, and set instructions for the GPT. It also details how to create conversation starters and connect the GPT to webhooks for automation.
What is the significance of the 'get request' example provided in the script?
-The 'get request' example demonstrates how to use GPT to fetch information, such as the number of new emails, from an external application like Gmail, showcasing the practical application of GET requests in automation.
How can users ensure their GPT is set up correctly for automation?
-Users can ensure their GPT is set up correctly for automation by following the step-by-step checklist provided in the script, which includes creating a GPT, setting up webhooks, creating automations, and testing the actions within the GPT.
What is the benefit of using the step-by-step checklist mentioned in the script?
-The step-by-step checklist benefits users by providing a structured guide to set up and test their GPT for automation, ensuring that all necessary components are in place and functioning correctly.
Why is it important to test the GET and POST requests within the GPT?
-Testing the GET and POST requests within the GPT is important to confirm that the automation is working correctly and that the GPT can successfully retrieve and send information to and from the connected applications.
Outlines
π€ Introduction to ChatGPT for Task Automation
This paragraph introduces ChatGPT as a powerful tool for task automation. It highlights how people often waste time copying and pasting information into and out of ChatGPT, but suggests that with the right approach, users can automate the process by staying within the platform. The speaker promises to show how to pull in relevant information from various sources (Google Docs, Sheets, emails, etc.), send data, and automate tasks like updating Google Sheets or creating documents, all without leaving the ChatGPT interface.
π§ Understanding API Requests in ChatGPT Automations
This section explains the basics of how ChatGPT interacts with external applications using 'GET' and 'POST' requests. The 'GET' request retrieves information, while the 'POST' request sends data to external applications. Examples include checking email through Gmail or writing a story and sending it to Google Docs. The speaker emphasizes that by using these methods, users can automate their workflows efficiently. Resources like a step-by-step checklist and a custom GPT are provided to guide users through the process.
π² Automating LinkedIn Posts with ChatGPT
In this paragraph, the speaker introduces a real-world example of automating LinkedIn posts by aggregating news articles and turning them into posts. The speaker reads artificial intelligence news from various sources and automates LinkedIn post creation using ChatGPT. The example involves setting up a 'GET' request to retrieve articles, having ChatGPT generate posts, and then automatically sending those posts to LinkedIn. The speaker walks through the process of building this automation step by step.
π οΈ Creating and Setting Up a Custom GPT
The speaker goes deeper into how to create a custom GPT. This includes defining its name, description, profile picture, and conversation starters. In this specific case, the GPT is designed to automate LinkedIn posts. The instructions for setting up the GPT to handle LinkedIn posts include prompt engineering, making 'GET' requests for article data, and organizing the responses into LinkedIn posts. The speaker highlights the importance of well-defined instructions and walks through the process of creating a GPT for the automation.
π Connecting Webhooks and Make.com for Automation
This paragraph explains how to connect ChatGPT with external applications through webhooks using Make.com. The speaker walks the viewer through creating a webhook and configuring settings to enable automations. An example involves aggregating news articles from various sources using RSS feeds and triggering the automation when a webhook URL is contacted. This part emphasizes the importance of creating a proper 'GET' request to fetch data from external applications and link them to ChatGPT for automation.
βοΈ Setting Up a Webhook Response for Automation
The speaker describes how to finalize the automation by creating a webhook response that sends data back to ChatGPT. This part of the automation involves structuring the response to include specific information, such as article titles, URLs, and authors, which can then be used to generate LinkedIn posts. The speaker provides detailed instructions for formatting the response and using the schema for the 'GET' request, ensuring the data is ready for ChatGPT to use.
π Creating and Testing the GPT Action
This section outlines the process of creating and testing the GPT action, which connects ChatGPT to the automation. The speaker walks through the steps of setting up the schema, uploading it into ChatGPT, and creating a custom action. The GPT action is tested to ensure that it can successfully pull in data from the RSS feed and generate LinkedIn posts based on the retrieved articles. The speaker also discusses how to modify the automation to refine the output format.
π Automating LinkedIn Post Publishing
Here, the speaker explains how to automate the actual posting of LinkedIn content. The automation now includes both 'GET' and 'POST' requests, allowing ChatGPT to not only retrieve information but also send posts to LinkedIn. The speaker provides a walkthrough of how to configure ChatGPT to format LinkedIn posts with titles and content and send them to a webhook. This is demonstrated by posting test data from ChatGPT and verifying the results on LinkedIn.
πΌ Finalizing the LinkedIn Automation Process
The speaker finalizes the process by refining the GPT's instructions to format LinkedIn posts appropriately. Adjustments are made to the prompt and schema to ensure posts are well-structured. The speaker tests the post request, confirming that the automation can send LinkedIn posts dynamically. The video concludes with the automation fully operational, allowing ChatGPT to fetch articles, create LinkedIn posts, and automatically publish them with minimal user input.
π Revising and Enhancing GPT Automations
This paragraph covers the process of revising the automation by adding post requests. The speaker explains how to add another HTTP method to allow ChatGPT to post information to external platforms like LinkedIn. The section provides instructions on how to modify the schema to incorporate the new method and dynamically send data, allowing users to automate both fetching and posting actions.
β Wrapping Up the Automation Setup
In this final section, the speaker recaps the automation process and tests the full workflow, which involves fetching articles, creating LinkedIn posts, and publishing them. The automation is now complete, and the speaker emphasizes how this efficient system saves time. The video concludes with an invitation to join the AI Foundations Community for further learning and efficiency gains using AI in personal and professional tasks.
Mindmap
Keywords
π‘Automation
π‘Chat GPT
π‘Get Request
π‘Post Request
π‘Webhooks
π‘Make.com
π‘Schema Ninja
π‘RSS Feed
π‘LinkedIn Post
π‘AI Foundations Community
Highlights
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Transcripts
chat GPT is amazing when it comes to
automating tasks but only if you know
how to use it right often times people
are left copying and pasting stuff into
chat GPT and outside of chat GPT and
ultimately that wastes time so in this
video I'm going to show you how you can
stay in your GPT and pull in relevant
information whether it be from WordPress
Google Docs Google Sheets social media
posts emails whatever it is you have the
ability to stay in your GPT click a
button and retrieve that information in
seconds you also have the ability to
send that information maybe you want to
send an email maybe you want to update a
row in your Google Sheets from your GPT
without leaving your screen maybe you
want to create a Google doc analyze a
PDF whatever it is you have the ability
to automate that and stay within your
GPT the entire time and in this video
I'm going to show you how it's done I'm
going to be giving you so many resources
I'm going to be giving you a
step-by-step checklist and I'm just
going to ultimately walk you through how
to do this and how to see success when
automating Tas ask in chat GPT listen AI
should be saving you hours of your time
right now if it's not then you're doing
something wrong that's why the AI
foundations Community was created it was
created in order to enable you to be
more efficient and more productive
whether that be tasks in your personal
life or tasks in your work life we show
you the steps to get there if you want
to learn how to leverage AI in your
industry to become more efficient and
more productive as a person then join
this community using the link in the
description or the top pend comment you
will not regret it before we get into
chat gbt and we start learning how to
actually automate things let's
understand real quick how it's working
under the hood and some of the
terminology I'm going to be using so the
red line is representing getting
information from an external application
the blue line is representing performing
actions on other applications okay so
you start off in your GPT this is big
chat GPT logo and you can either send a
get or a post request a get request is
the red line because you're getting
information from other sources the post
request is the Blue Line because you're
posting information on other sources or
to other sources so let me show you a
quick example of a get request I might
prompt to my GPT how many new emails do
I have today and it will send that
request to make and run through an
automated Gmail process on make because
it connects to Gmail and fetch my email
contents and how many emails I have and
the body content of those Etc and it
might form back a response of you have
five new emails an example of a post
request might be me saying write a story
about a dog and send it to my Google
Docs when complete my GPT would take
that request in the form of a post
request which I'll show you how to set
up contact make with the content that
I've provided the story about the dog
and send it to a new document within my
Google database and what I've even
provided for you is a step-by-step
checklist down in the description that
you can just follow along as we're doing
this video together for everything you
need I've even provided you a custom GPT
for this system to help you when I'm not
here to help on on the video so first
you need to understand what you want
automated and I'm sure you have some
ideas right now uh even just by watching
this first part of the video but let's
say for me I don't have much time to
create LinkedIn post but I read a lot of
artificial intelligence news articles
and I have specific websites I like
going to so for me a good example of
creating a GPT that is completely
automated and post on LinkedIn for me
would be step number one using a get
request so I can aggregate all of my
news articles and bring them back into
chat GPT so that chat GPT can
automatically create LinkedIn post for
me based on the relevant content from
the news feeds that I like so I'm
pulling articles into my GPT creating
posts using chat GPT that's why we would
go to chat gbt for this and then I would
send off those posts to my LinkedIn
automatically that's what we're going to
be building today so let's get right
into it step number one what we need to
do as you can see on our GPT automation
checklist is we need to create our G PT
so we need a name a description a
profile picture instructions and
conversation starters if you want a more
in-depth guide on creating this version
of your GPT like creating a very good
GPT with amazing instructions I'll leave
a link to that video in the upper right
hand corner where I go much more in-
depth on that so real quickly I'm going
to create this GPT and then I'll report
back to you once I'm done and kind of go
through what I did what I'm going to do
is in the upper right hand corner I'm
going to go to my gpts and then I'm
going to select create a GPT here I can
give it a name description instructions
conversation starters and a profile
picture and again since I am automating
my LinkedIn post I can give it a name of
the LinkedIn master and then I can give
a little description of what it does
this is actually an image of the
LinkedIn logo that I got generated for
this on Gro which is another language
model I can hit open and just like that
we have a profile picture name
description and now we need instructions
and this is kind of going to be
instructions for how your GPT needs to
run all the actions you want it to
complete and how it's going to contact
your web hooks so for that I put you are
a LinkedIn growth specialist now this is
basics of prompt engineering if you
don't know this yet then you definitely
need to learn it before you get into
fancy automations but I basically give
it a roll and tell it its job I tell it
what it's going to receive and then I
say right here when I say fetch articles
contact my web hook and get me the most
recent articles on AI this is going to
be a sendoff command to start the get
request which is going to be important
as you can see it says when I say fetch
articles in order to make my job easier
I can copy fetch articles and make a
conversation starter so now I can hit
this button and say fetch articles and
it will automatically run through that
process for me since I set it up like
this in my instructions and then I
basically tell it to receive the URL
read the content and create a LinkedIn
post and I give it a custom output
format for each LinkedIn post now I can
go back to our GPT automation checklist
and step one is complete we have a name
description profile picture instru
instructions and conversation starters
next this is where the real fun begins
we need to create the connection in
make.com by creating a web hook and
creating our make.com Automation and a
lot of the times it'll take 10 or 20
minutes to create an automation but it
will save you hours of time on the back
end and I even give you a GPT to walk
you through this step by step and it's
right here in a link so it's called the
schema ninja and I created this just for
this video and what you have the ability
to do is hit get request or post request
and that will actually send off a set of
instructions to the schema ninja in
order to help you create that so if we
go back to my instructions what you'll
notice right now is I need to first set
up a get request because right now I say
when I say fetch articles get me the
most recent articles on AI so how am I
going to do that because I need to get
that information back into chat GPT
therefore it's a get request so I can go
to my schema ninja and select get
request and it's going to walk you
through step byep what you need to do in
order to create this request as you can
see step one create a hook and make and
then change it to these settings right
here I even give example images for each
step so you can see what I'm talking
about as you're using this GPT but keep
in mind I'm using a free make account
for this okay I'm not using anything
paid other than my GPT plus plan which
I'm sure if you're watching this you
might have right now what we want to do
is we want to select create a new
scenario and then follow the
instructions from the schema ninja so I
need to create a web hook and change my
settings to get request headers yes and
get HTTP method yes so so I can do that
by once I create a new scenario this box
will pop up I can type in web Hooks and
then I want to select custom web hook
and here you need to add a web hook so
I'm going to hit add you can give it any
name you want I'm going to name it
posting for
LinkedIn beautiful I'll hit show
advanced settings and turn on these top
two and then hit save then I can hit
stop and okay beautiful so now we have
the ability to contact this specific URL
in order to start an automation that
follows this we can start an automation
by adding modules here and connecting to
so many different apps like Facebook for
example or Instagram and we have the
ability to download Media get media we
could contact notion and create database
items we could contact Google Sheets for
example and we can create rows we can
create sheets create sheets from a
template so as you can see there's
multiple different things you can do
after this web hook URL is contacted
with our GPT which I'm going to show you
how to set that up now so you can just
keep walking through this we've created
our web hook in our settings so I'll
just say complete and it's going to keep
giving you step-by-step instructions for
what you need to do so now it says
create your automation using make
modules so the tool I use for
aggregating my news articles is a tool
called RSS doapp this allows me to
create feeds and connect with
information from multiple different
sources I have articles pulling in from
MIT news artificial intelligence news
open AI research and Tech crunch so this
URL Aggregates every new post that comes
from those websites I can actually
connect to that and make so once this
web Hook is triggered I can type in RSS
and then I can retrieve feed items from
a specific feed that I create so I can
put in my URL and then I can have a nice
custom date from and date to most of you
won't be needing this complex of a
format for date from and date 2 but I
just want to set this up so I can be
receiving information from yesterday
maximum number of returned items how
many articles do I want coming in at
once maybe I only want five I can hit
okay and now I need to format this data
so that it's ready to be put in a web
hook response so I have this set up I'm
pulling in the URL title and author I
can hit okay and now I can aggregate
this data in order to pull in each
article CU right now it would only pull
in one article so I have to make one
text strand for all of them so I did
that that was very very simple in the
text aggregator side of things and many
of you won't have to do this complex of
tools in order to aggregate some
information but next after we've created
our automation we can take a look at
everything we've done so we've created
our web hook and now we need to finish
creating our automation so we can do
that by just talking to our schema and
just some more I'm just going to say
complete right there and now the next
step after we have our automation done
which is these three steps right here
what we need to do now is create a web
hook response and map our data so the
web hook response is important because
this is what your GPT is actually going
to receive so if I go here and I select
web hooks again and I select web hook
response in this body field this is what
information is going to be given to your
GPT so I've set up this information in a
way to where all I need to do is get my
text from my array aggregator and if I
have five articles then I need to make
five responses of that array aggregator
in the body of that web hook response
but you can just put normal text in here
too maybe you just want to put hey with
a couple exclamation points this
response will be received back in your
GPT but when you're using these
applications you actually have the
ability to map specific data to your web
hook response and this is where the
dynamic ability of your automation comes
in play here so I can hit okay beautiful
now we have this automation pretty much
all up and running we've created our web
hook response just as the schema ninja
has told us we have an example image
here too now I can just say complete
what do we do next now we need to create
the schema for this get request so we
can actually use chat gbt to pull in the
information to our GPT here which in
this case is the LinkedIn master so if I
go back to the checklist actually what
we've done is we've created our
Automation and now we're on the step
three which is creating our GPT action
so we need to go back into our GPT that
we've created and actually find a way to
connect to this automation here so the
schema ninja told us to create open AI
schema for the get request take a
screenshot shot of your web hook
response body and upload it here or you
can just give it the information it
needs in order to create that schema so
that it knows which information to pull
for now I can just go to my tools here
and I can paste in a screenshot of this
information that I want chat gbt to be
pulling in url title and author so we
need to take a screenshot of the
information we want pulled in or we can
just tell it maybe I want article URL
article author article content whatever
it may be you can give it all that
information that it needs in order to
create the schema then you can tell it
the goal which one and two kind of go
together this is just to get an idea of
how to create your schema for the get
request and step number three it tells
you to provide it with your make web
hook URL that you created in the first
module right here so this URL this blue
URL under your web hook action so I'm
just going to keep following this
stepbystep process I'm going to upload
my screenshot of the things that I
wanted pulled in or again you could just
tell it the things you want pulled in as
well I just want to show you an example
of this multimodality and then what you
want to do is copy your web hook URL the
entire thing and paste it in so I can
say I've provided everything create my
schema and send it off and it's
automatically going to create your
schema for you in the Json format that
you need this is what you're going to
paste in to the action section of your
GPT this is that long string of text
that is always very intimidating
whenever you want to automate something
so we we go back to our GPT now and we
scroll all the way down to the bottom
where it says actions down here we have
the ability to hit create new action
here we need to upload the schema that
was just created by the schema ninja
based on all the properties you want
pulled in from your automation so I can
copy this code head back to chat gbt and
paste in the schema just like that we
now have a get request with our specific
path our operation ID and it's very
beautiful so now we can even test this
but before we test it we can just go
back to our schema ninja and we can say
complete now that we've uploaded this
there was no errors nothing went wrong
we have a beautiful action in here ready
to go and this right here when we hit
test is going to contact this web hook
which will trigger the automation we
just created and after it runs through
this three-step process in the middle of
the red modules what it will do is send
back what it got from running through
that process okay so I'm going to turn
this on in the bottom left hand corner
and then I'm going to hit save on my
automation because once you hit complete
in your schema ninja that's what it's
going to tell you to do is to save and
test your information then we can send
off a test so I'm going to hit test and
what it should do is pull in all the
information that we're getting from my
RSS feed which is an external app that I
wanted connected so I'm going to hit
always allow up here and it's going to
talk to this web hook it's giving me the
post now from my RSS feed Fe so this
information is very custom because it's
coming from my specific feed that I
wanted in that external app and it's
actually making LinkedIn post out of
these right now so the data came in but
maybe it didn't come in in the format
you want or maybe it didn't come in in
the exact way you wanted as long as you
get response received with a status code
of 200 then it means your automation is
working you have the ability to change
whatever comes after this web hook
update your schema that you've created
with the schema ninja and actually pull
in whatever information you'd like based
on this web hook URL as you can see
though it's just giving me the post and
it's not showing me the title author and
URL first maybe first I want to actually
read the article then tell it to create
a post based around it so I can change
the instructions and edited around at
this point but we've completed our get
request so as you can see I've added in
some very basic instruction updates I
say before you create LinkedIn post
provide me with the following author
author here title Title Here url url
here then ask me which article would you
like to create a LinkedIn post around
that way I have a little bit more
control and it's a little bit more of a
process rather than just creating
articles and post right from the jump so
now I can go back and I can test this
again by hitting fetch articles now that
we have our get request set up since we
set up the instructions to contact the
get request once we say fetch articles
our conversation starters will be
working so I can hit fetch articles and
test this out again to see if it's
pulling in data how I want it to so as
you can see now it's coming back with
everything I asked for it's giving me
the author and then the title and the
title is actually in the form of a
hyperlink which is beautiful so now I
can actually click on these articles and
go to the source where they're coming
from and then it ask me which article
would you like to create a LinkedIn post
around I could just type out a number at
this point I could just say number three
for instance then it's actually going to
create that post around the article so
it's starting off with what if we could
design proteins to revolutionize
medicine and Beyond going a little bit
in depth and then having a CTA and then
it asks me the question would you like
me to send this as your LinkedIn post I
could say yes but we don't have that
action set up yet so if we go back to
our checklist we now have the ability to
check off the remaining things because
we've created our GPT action and we've
tested our GPT action we've grabbed test
data from the get request now what if we
actually want to send these LinkedIn
post well then we need to revise our
schema because our schema right now if
we go to our actions only has one method
of using the HTTP request which is get
right now so we only have one avail
action right here and that's to get web
hook data or in other words get our
feeds into our news articles from that
app what if we wanted to send this well
then we would need to add to our
Automation and we'd also need to revise
that schema in order to make it
available to have another method of HTTP
request and in order to edit this first
we need to have test data with our web
hook so we can dynamically map fields
and the web hook data needs to be the
LinkedIn post we need to figure out a
way to pull in Dynamic LinkedIn posts to
this web hook so we can do that very
simply first we can go to our schema
ninja GPT and type in a new prompt and
make sure you're staying in the same
chat thread for this so what I'm doing
here is I'm basically staying in the
same thread because we know that this
schema is working and this GPT is
designed to create schema that works so
what I can do very simply is add in
another http method to the schema that's
already working and that and it already
exists and then later we can change
around our automation after we send it
some test data but I say using this same
schema add in a poster request with the
get request I want this poster request
to be able to send my content to the web
hook the content in this case would be a
LinkedIn post help me revise the web
hook in order to be able to add another
HTTP method of post where I can send
information to my web hook in the form
of a post I keep reiterating in the form
of a post so at this step if you want to
not only get information into your GPT
but be able to post it elsewhere which
some people are fine with just pulling
in the information and then working with
it and then doing whatever with it later
a lot of the times that's the hardest
part is getting that information in but
we can actually revise our schema to add
a post action to do something else so I
can send this off I recommend just using
a similar prompt if you're trying to add
to your schema to get a post request
query but what it's going to do is it's
going to use the same URL it's going to
use your same web hook path except
underneath get it will have your entire
get operation and then it's going to go
into a post operation so we're going to
send a LinkedIn post to our web hook
very very cool it gives us our updated
schema so right away what we can do is
we can copy this updated schema that it
gives us go to our GPT and actually
paste it in but first you want to delete
your old schema which might be a little
scary but then you can paste in new and
what's going to happen is you're going
to see another method down here so now
we have the ability with our GPT to get
information and post information but as
you can see we have some required Fields
down here it says post title and post
content this is what we want our GPT to
format our information with we want a
post title and post content in order to
actually send these posts to our web
hook so now we need to go edit our
instructions to ensure that whenever it
creates a LinkedIn post it formats it in
this Json format and it actually with
our schema ninja gives us that format
that we need and it gives us
instructions for a poster request so
what I can do is I can just copy these
instructions head back to our GPT and
then go paste those instructions in our
instructions so I can leave these at the
very bottom and these are going to be
instructions for the Post request when
using this post request you'll need to
send a Json body that contains post
title I can put those in quotations and
post content Fields because you need a
structured way to send your data to your
web hook in order to be able to use that
data dynamically so that's why we're
doing it in Json format so underneath
these instructions for post request I
can then put that example Json body I
can say here is an example of how to
structure this data and I can go back to
the schema ninja and copy this code the
example Json body for post request and
if it didn't give this to you just ask
for this stuff and the schema ninja is
really good at doing that for you and
then I can paste it in beautiful we have
the structure of how this should look I
can then hit close and now we can go
test our post request to make sure it's
actually running so I can go to actions
and under available actions where it
says post I want to test this so I can
hit test on post and it will send an
example post to your automation on make
just so we have data to pull from when
we do create the rest of this automation
I can hit confirm and I can kind of run
through this process I'll just say
article three and then I can say post
and when I send that off it should
perform the action of the post method
and it says the LinkedIn post has
successfully been sent what I'm going to
do now is actually map this data to our
web hook and create a LinkedIn post
around it like physically create the
automation that we can use from the data
that we're receiving from our GPT here
so I'm going to unlink in between right
here and I want to have a router because
a router is going to allow us to go to
different methods so I can select router
and this is going to be the router to go
to our get request this will be a
fallback method and I'll explain what
that that means in a minute but now I
can add the Linked In and once I hit
LinkedIn I can just do create a user
text post and add that to the router so
now we have two different routes to go
the post request method and the get
request method in order to make sure
that it's filtering out correctly what
we need to do is set up a filter on our
post request we can select the wrench
hit set up a filter label this can just
be condition setting and then for
condition we can have meth
is equal to post and we can just make
equal to case insensitive and then I can
hit okay so now if it is a post it will
go here first and this will be a
fallback route we can set up this filter
in between the RSS feed and the router
to be a fallback route and this will be
the first condition it sees and checks
if it can go to next what you need to do
is you just need to hit send data again
this is just going to make sure that
your data is being sent in your test
feed and I just do this in order to make
sure the fields are pulling in because
sometimes when you go here and your
automation isn't saved when you try to
map in your content to the dynamic
fields in your web hook they won't pull
in so what you need to do if it's not
pulling in is save your Automation and
hit this little back arrow and then go
to your GPT where you've been testing
and just hit send data again and then
when you click back in here you should
be able to dynamically pull in that
content so now I can pull in post
content just like that so this would be
an example of setting up a post request
we need to be able to pull in
information dynamically from our web
hook that's coming from our GPT like
shown I can hit okay I can save this
Automation and now we can put this to
the test I'm going to go to my checklist
check off the post request again you
don't have to do a post request optional
depending on your Automation and then
what I can do is I can come to my GPT
now that all the testing is done in the
upper right hand corner I can hit create
and then I can make access invite only
and then I can hit update or I can
create it for the first time if that's
what you're doing then I can hit view
GPT next I can just walk through this
process and do it so I can hit fetch
articles then I can hit always allow on
that web hook because it needs
permission to talk to it and that's
going to give me all the recent articles
from my feed that I can create post
around based on the last 254 hours so
maybe I could say post number three and
send that off and now we have this
automated process to where I don't even
have to leave my GPT screen and it's
going to give me a post draft it's going
to give me this beautiful LinkedIn post
based on the article and I could say
revise it to attribute content to the
author at the end of the post you can
even revise these posts and you can
revise your content and chaty BT is
basically your assistant now you can ask
it to go get things for you then you can
ask it to post things for you so I'm
telling you to provide a link of the
article at the bottom instead of the
inspired by comment because I don't want
it to just say content inspired by I
want it to provide a link to where I am
uh getting these thoughts or these ideas
from so now it ask me would you like to
send this post to the web hook for
LinkedIn posting I can say yes
absolutely so as you can see I'll just
have to hit confirm really quick very
easy and then it's going to post that on
LinkedIn your LinkedIn post has been
successfully published it used the
information that it got from here very
quick and a very automated system as you
can see if I go on my LinkedIn and go to
posted just now I can click this and it
did post literally everything in a
matter of seconds just like that that's
how Innovative this is that's how
efficiency works within AI now if you
enjoyed this and you want to even become
more efficient then again I recommend
the AI foundations Community to anybody
I mean since just recording this video
we already have two new members in the
past hour people are joining in order to
leverage efficiency with AI and people
that are applying this stuff in their
business and their personal life are
succeeding with it there's so many
different Industries in here leveraging
artificial intelligence and you could be
one of them so if you want to learn more
cool things like this to save you hours
of your time using this technology of
the future then I don't want you to fall
behind and I want you to join the
community we have so much to offer there
live calls courses Etc in order to get
you from A to B but with that being said
I hope you enjoyed this Automation and I
hope it helped you if it did Please
Subscribe and like this video I will be
coming out with more content like this
if you'd like me to go more in depth
just let me know I be happy to answer
your comments record more videos
automate more things so I can help save
you time with AI all right I'll see you
in the next video
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