All right.
We're back here in NH and I'm going to press sign in to come back in as the account that we just created
a few moments ago.
This comes up.
That was the name that I gave my my instance.
I click open instance and here it is.
This is looking now at the the the home screen if you're still on the previous screen we were on before
with that workflow, you can just press this home button right here and you get to this screen, the
home screen for this instance.
And you can see here that it has, uh, my workflow.
This is the thing we created earlier sitting there.
We're going to start again and create one from scratch like we did before and use open AI this time.
Okay.
So follow along with me here.
And tomorrow we'll explain what all the different terminology means.
We first press Create Workflow right here.
And we get again this fresh screen a new screen for us.
We'll add a first step.
And again we are going to add this thing here on chat message on the right.
Click there and then remember what you do next.
You press escape.
There we go.
Or you click that back button at the top left.
So here we are now going to press this plus button.
You remember what we do next.
We click on AI.
And next we do AI agent.
And here is our AI agent.
And next it's either back to canvas or it's escape.
Here we are back on this canvas.
All right.
The chat model is the first thing for us to select.
You may remember last time we did open router at this point.
And you may do that again should you wish.
Uh, but I'm going to this time do chat open AI, which I do by typing open AI.
And there we see the open AI chat model and up it comes.
Uh, there is also, by the way, if you're if you're starting for the first time, you can create get
100 free open AI API credits.
At least I can at this point by pressing this.
I don't know if you see that too, but but I'm going to ignore that for now and just push on and use
the credits that we just set up.
Okay.
So now I'm going to again click here and say create new credential, just as we did with Open Router.
And again just as we did with Open Router I'm going to paste in here that API key that I still got in
my clipboard when I copied it just a few moments ago.
I do paste, I say that and now I'm going to press save and we'll see what happens.
Credential successfully applied.
Testing successfully tested.
It works.
If it didn't work for you, remember just go back and do it all again.
Create a new API key, copy it, paste it straight in here.
Don't go through another editor.
They can cause trouble.
That's the way to make sure you've got a good API key.
All right.
We are now set up.
No thank you.
We're now set up to be using open AI.
Okay.
Now in this box right here we're going to keep this to say from list here.
And this one here is the list of all of the models available on open AI.
Now there's lots of models and the as of right now, for me, the fanciest one is GPT 5.1.
But we're gonna stick for now with GPT 4.1.
Mini looks just like that.
GPT 4.1 Hyphen Mini.
You can either you should be able to find it in this box, and the reason I choose that one is that
it's really fast and it's really cheap, and it's just a great one to use to start with.
There's an even faster, cheaper one called GPT 4.1 nano that we could also use, but but we'll use
mini for now.
It's still very, very cheap for simple messages like this.
Okay.
And so now how do we get back again?
We get back either by clicking here or by pressing escape.
And what we should now be able to do is click here on the bottom left in the in the in the chat section
and we should say hi there.
And off it goes.
And it's thinking and it's processing stuff is happening and we get an answer back.
Let me make this a bit bigger for you.
An answer from GPT.
Hello, how can I assist you today we just connected to to open AI and we got back a message.
And now I want to show you something that you may not be expecting.
Look at this.
I'm going to say hi.
My name is Ed and off it goes and thinks you can see it doing its stuff.
And it's thinking and it's thinking.
Hi editor.
Nice to meet you.
How can I assist you today?
Okay.
I'm going to say hey, what's my name?
So I have to click here.
Hey what's my name?
And it's going to think and it's going to do its stuff.
And it's going to say I don't know your name yet.
Ha.
Were you expecting that?
It's like what?
So this is a key learning moment.
Remember what I said earlier when I was defining an LLM and explaining that we sometimes get fooled
by using ChatGPT the product.
It gives it lots of lots of a sense of having things like a memory while you speak to it.
The LLM itself, OpenAI, GPT 4.1 mini.
It's something which is entirely stateless every time you call it with an input, it's a new input.
It doesn't know about the inputs that came before.
The way that we can give this illusion that it remembers what's going on is by adding software around
it.
That gives it things like a memory.
And that way it will know that if I say, my name's Ed, and then I ask it what my name is, it's going
to remember it's Ed.
So if we were writing software, we would have to build some code to have memory of the people.
We'd need a conversation history, and the N810 gives us that functionality out of the box really easily,
just with a couple of clicks.
Okay, so here's how we do it.
We click just below memory here.
You probably guessed this was coming.
Click there and then you can see it says for beginners.
That's nice of it.
Simple memory stores.
So no credentials required.
Let's use that for now.
Click in simple memory.
Press escape to go back.
Here we have it.
We have this simple memory.
Uh, and by the way this this box has come in yellow like this to represent the fact that something
changed since we last ran it.
So so it's something that that is potentially not in sync with the latest functionality.
That's why I'm going to press.
Do you see this little this little arrow at the top here.
Reset chat session that's going to clear everything out.
It's going to allow us to start again and run our little test another time.
Okay.
Let's see.
Let's say hi there.
Off it goes.
Always watch these, uh, these pictures here as you see it, thinking.
Hello.
How can I assist you today?
Uh, say my name said my name's Ed.
Okay, off it goes.
It's thinking, it's thinking.
It's doing stuff.
Hi, Ed.
Nice to meet you.
How can I help you today?
What's my name?
Here we go.
Off it goes.
You can see things are happening.
Stuff is happening.
Your name is Ed Ha.
Success.
Uh, it may not seem that amazing.
And you may be thinking I could do that in ChatGPT.
But remember, we are building bits and pieces of the ChatGPT product right here.
That's what we are doing.
So we have just done something super simple.
We've given this ability for the context of the conversation to be held so that we can have this conversation
with an agent.
And if you were coding, this would be just a few lines of code, but it would be a few lines of code.
What we've got here is we've done all of that by connecting together boxes and lines which which we
will be doing a lot of over the course of the next few weeks.
Okay.
That's that's nice.
It's time for us to add a tool.
Okay.
I would like you please to open a new browser window and go to a web page called Market Stack.
Market stack.
Here we are.
Now you will have I'm already logged in.
So I've got like a dashboard thing here.
But you will have a sign up button that will allow you to sign up.
And you go in and you select free.
There's there's different types of accounts.
You want a free account.
And when you've done that it takes you to your dashboard page as soon as you've signed up.
It's very quick and I can't take you to my dashboard page because it shows you your API key right there
in the center in big letters.
And then you would have my API key, but you should take that key and copy it to your clipboard.
Uh, there's really it's very, very streamlined.
There's very little to it.
And now anyway, you're starting to be a pro at setting up these accounts and API keys.
We're going to be doing a lot of them in the next few weeks.
But do that.
And now you have an API key to the free service market stack.
It should be super simple.
Get that key copied to your clipboard and I'll see you in a sec.
Okay, here I am back in NAS and I pressed that button to clear my chat.
The button that's just around here.
Now, we come in here and I'm going to press this plus button underneath tool.
I press plus and up comes a list of tools on the right.
And I'm going to type the word market and market stack tool appears there.
Click on that.
Up it comes.
Go to this credentials connect with drop down and select Create New Credential.
There's an API key field and paste in that as before and then press save.
Uh and it says credential successfully created saved.
And now you press escape.
We go back here.
No thank you escape again.
And we're back here.
And it's got that red thing.
Oh sorry.
They come back in here.
I'm sorry.
Double click again to come back in here.
There's just a couple more things to do.
Uh, in this, uh, leaf tool description is set automatically in resource.
Leave that set to end of day data in operation.
Leave it at get many.
That's great.
Under ticker.
This is where this tool needs to be told.
Which stock ticker are we looking for?
This is about looking up stock prices if you didn't figure that.
And here there's a little funny magic button to the right that says let the model define this parameter.
Click that and it now says defined automatically by the model.
This is saying we are going to ask the LM.
We're going to ask GPT 4.1 nano to decide what stock ticker it wants to use when it uses this tool.
And now you can leave this this leave this as limit 50.
There's one more thing to do which is that this add filter drop down here.
Click there and just click latest like that and then turn that on like so.
So you went to add filter latest and you turned it on.
And when you've done all of that you can now press escape.
And now that that angry red symbol has gone and we're ready to try this out.
This is a tool.
Get many end of day data in market stack.
There we go.
We have a model.
We have memory.
We have a tool.
Let's try this out.
And so here I go.
And I say hi there.
Clicking in the chat down here There's lots of whirring, lots of thinking.
Hello, how can I assist you today?
I'm going to say, um.
What?
Please, please tell me the, uh, um, end of day equity price for, uh, what?
Should we go with Google?
Let's do that.
Let's run.
Watch what goes on here.
Watch, watch, watch.
Things are happening.
You do see that?
Just suddenly swizzled.
You can see some information here.
The end of day market price for Google on the 8th of December was 31 3.72.
Wow.
We just had an LLM.
We just had a conversation with a model, and it had the ability to look up stock prices.
And it did it using a tool.
And it all happened like over here with colors flashing.
As our workflow came to life, the AI agent connected to OpenAI, it used its memory to keep a conversation
going with me, and it looked up the Google stock price in market stack, and I can continue the conversation.
I can keep going.
I can refer back to what I've said before because it will it will have that memory.
And and you can try this out yourself and see how you have given this capability to a model.
And I hope this gives you a sense of just how much more we can do with this.
This is really our staging ground.
This is the starting point we will be building from this simple beginning.
An agent that runs with tools will be using this to build more and more sophisticated business capability
in the coming weeks.
Okay, I'll see you back for the wrap up.
Congratulations on building your first business workflow in ten.
Simple, but a stepping stone to much greater things.
I want to mention that that you may not know this, but.
But you've got something extra with this course, whether you like it or not.
And that is.
You got me.
Uh, I come with the package.
Uh, I'm available to help you if you get stuck.
That's what I'm here for.
I you can you can always reach me through the Udemy platform.
You can also reach me in LinkedIn.
This is where I am.
You can read all about Nebula and my other background and the other courses, uh, that I, that I teach
on or where I speak on my LinkedIn page.
And you can also connect with me.
Some people are coy about connecting with them on LinkedIn, and they say, you know, if you want to
connect with me, you must mention where you knew me.
I'm not coy at all.
I love connecting, so by all means, connect with me.
Reach out.
This is where you'll find me.
You can get hold of me, and, uh, I will, uh, if you say hi to me, I'll say hi back.
Uh, it's not an agent.
It's definitely me.
I do sometimes use copy and paste.
I reserve the right because I say similar things that I do sometimes, like paste in half, at least
half of my answer.
But it's always me at the helm, always me pressing that button or saying saying hi myself.
So do connect with me.
You don't need to say hi if you.
If you don't, I'll connect with you.
With you for sure and reach out to me by email or on Udemy Q&A if you've got questions.
Questions sometimes get buried in LinkedIn, so there's something's better, especially if it's like
a detailed technical question to do it in Udemy or by email.
But but either way, I will I will be responsive on all channels and I love hearing from people.
I love this community, so take me up on it.
I come with the package, connect with me.
If I haven't said that enough, I'll say it like another 100 times until you.
Until you're beaten into submission.
You connect with me just to shut me up.
Uh, and, uh, do ask questions anytime.
That's what I'm here for.
Also, as you make projects, as you bring things to life with Nh10, then post about it on LinkedIn.
Describe what you did bring up, take a screenshot or show some of of what you've accomplished.
And if you tag me and make it relevant in some way, then I will weigh in and add to it, and that helps
to amplify your accomplishment so that perhaps future clients might see that and might be interested.
So.
So I can help with that.
And I love doing that.
So take me up on that too.
And similarly, if you see that, that other people from the course are posting things that I'm weighing
in on and you see that in your feed because we're connected, then I would really appreciate it if you
weigh in as well, do do like it and add your comment, because that helps amplify the community.
And that's great for everyone.
That's part of this program.
Okay.
And with that, can you believe it?
We have already completed the first day.
The first day is marked off.
One day down, 14 left to go.
You're not going to believe all the things we're going to build, but that means you're already 7% of
the way through this program.
Many congratulations!
I can't wait to see you tomorrow.
And we're going to get deeper into the theory of n810 and agents.
I'll see you then.