And welcome to the grand finale.
I should mention that in Pipedrive I have.
I have changed the name of one of our people to be Tom Jones, because I thought it would be bad if
I if I had to try and present.
I was someone that I'm not in this, uh, so.
Well, I'm not Tom Jones either, but.
But you know what I mean.
Uh, let's, uh, let me me call this number right now as the, uh, famous singer Tom Jones, and we're
off calling.
Hi.
Thanks for calling account AI.
Who am I speaking with, please?
Uh, my name is Tom Jones.
Thanks, Tom.
I've opened a new Deal record for you in our CRM.
What time works best for your demo?
We aim for 2 p.m. eastern time on weekdays, but I'm happy to schedule it whenever is most convenient
for you.
Yes.
I'd like 2 p.m. Eastern on Tuesday, January the 6th, please.
Booking your demo now.
Your demo with account AI has been successfully booked for Tuesday, January 6th at 2 p.m. Eastern Time.
You'll receive a calendar invitation shortly with all the details.
Thank you for your interest and we look forward to speaking with you then.
Thanks.
Bye.
Success!
I can't believe I felt the need to say thanks bye at the end, because it was so engaging.
And the thing that you don't know that I do know that you're about to know, is that during the course
of that, while I was speaking and looking at my phone in front of me, I was also getting push notifications
while it happened.
So I can tell you that I am the proud recipient of two push notifications that came through while I
was on.
One of them saying created a deal and the other of them saying successfully scheduled a demo.
Booked Tuesday, January the 6th, 2026 with Tom Jones.
That is really cool.
And now we have to dig into the data to check for ourselves that it worked well.
Let's start in Pipedrive.
We come into Pipedrive.
If we go into the section on deals, we'll find that in addition to the Rob Carter deal from before,
there is also now a Tom Jones deal.
It was created and that worked great.
So that's that's good to see.
Now time to look in the calendar okay.
And if we head over to the Google Calendar you will see that we have the old one on the fifth that we
booked before with Tom Jones.
And now we also have on January the 6th another demo with with Welsh singer Tom Jones.
Uh, also also at the same time and at the zoom address and with all the details filled in as we wish,
just missing the actual invite to the email itself, because I withheld that part of it.
Just just to keep it as a, as a demo and not not send emails to people out in the internet.
But but you for sure could add that in, uh, but for me, this means that I'm very happy to declare
victory on this project at this point and very satisfying seeing all of the data built, everything
come together.
The CRM updated, the demo booked, uh, and yeah, I will tell you, hand on heart that this agent
number two.
First time, first time a charm.
It just it just worked like that.
There was no behind the scenes quickly coming in and fixing, uh, like there was with with with the
first, uh, first agent.
This agent worked right away.
And I'd love to say that's credit to me and my careful attention to detail, but actually it's because
I would I would argue it's because ten and 11 labs are built for this kind of thing.
They're built in a way that is bulletproof and encourages you getting things right.
There are a couple of points you can trip up, like the names of the body fields and making sure you
have the right the right webhook URLs.
But as long as you get that right, it just works as it did for us.
And you can deliver tremendous business impact in like an hour.
And here then, is the final picture of the architecture.
We built the two main agents, business development manager and account executive, with their three
and two Subagents all running together, representing six different external integrations representing
seven different MLM calls.
There was a lot that went into this and it worked so nicely together.
And as I say, the big takeaway for you is that building an infrastructure like this, with this many
integrations, integrations are hard.
And with this kind of working with unstructured and structured data and making a number of different
decisions based on it and being able to achieve this, this is something that could have been months
of work in the past, and with a product like Nan, along with a beautiful product like 11 labs together,
we're able to accomplish this in a matter of hours and in some cases, in a matter of minutes.
We were able to put pieces of this together.
And and to me, that is everything.
And that is hopefully something that has blown your mind as much as it's blown mine.
As I say, if I dare to say I want you to think of this like a canvas on which you can build like the
canvas itself.
This.
This is something which is a starting point.
It's.
You probably already think of a number of flaws with this, particularly the way I read in all the people
from the CRM, the way that the scheduling is a bit janky, and the way that it doesn't actually send
the invites to the person themselves.
But all of these are absolutely extendable, just using the same techniques and just being sure to carefully
test at each point.
And that's what you should do.
This is something that you can turn into a business machine.
The the messaging with the person that's that you're sending the email to that could also handle incoming
emails.
You could have it operating across a slack channel and have it be in a slack conversation with people,
nurturing them through until the demo is booked.
This this can be turned into a complete automated sales engine.
So you sit back and you just watch the demo meetings coming in and hey, maybe you could have an agent
that gives the demo and then just sit back and watch watch the revenue rolling in.
Even better remembering, of course, all the way through to to to test as you go to evaluate the effectiveness
of each of your agents.
Always keep a careful eye on the evals and on achieving your business goals, and this could be a product
that you build yourself for your own business.
Or of course, it could be something that you offer to build for other people.
This is something which which translates to so many different businesses.
You could set up an AI automation agency that is a sales machine that you build and replicate this kind
of structure to, to be suited to different businesses.
Maybe you add in a Rag workflow as well so that it has specialist knowledge, domain knowledge of your
client's business.
Okay, that's enough on the capstone.
I hope you loved it.
We've got two minutes now to wrap up the whole course.
So don't I know you're very tempted just to just to stop now.
Forget the nonsense at the very end.
But no, this is good nonsense.
Hang on in there with me.
I want to remind you that we've been through three weeks together, and it feels like a lot longer because
we've packed in so much learning into three tight weeks.
Let's look at them.
Week one was called automation.
Week two was called acceleration.
Week three amplify.
In week one we were building foundations.
We were dealing with our first data integrations, and we ended with that beautiful portfolio, Rebalancer
when it logged into Google Sheets and you saw it rebalancing an equity portfolio.
Love it.
Week two was when we first introduced 11 labs, the two different ways you could integrate.
And then I went through Rag.
I probably told you about rag like a million times.
Just be sick of rag.
But we went through rag.
We used supabase and we, uh, we had vectors being ingested, and we ended up with the expert product
voice agent that you could speak to about products that was reading from a Google sheet, or at least
that had been read into a vector database from a Google Sheets, uh, rag plus voice agent solution.
And then week three is when we went advanced, we covered some OAuth two stuff we deployed locally.
At the beginning, it seems like an age ago we deployed to self-hosted version of HN.
We went through MCP the couple of ways of using it.
Context engineering and subagents.
I had some rants there yesterday, and then today we polished off the capstone project, and I don't
need to remind you about that because you're still smiling, I hope.
From from everything that happened.
And that means this is the moment I can mark the whole thing as complete.
It's a clean sweep.
You've done it all, and you get the Golden Cup at the end of it.
Congratulations.
You have completed the entire three week course.
Everything here is done.
And now you may be thinking to me, okay, but we didn't cover this, which I'm really interested in.
Maybe it's loops.
Maybe you want to know about merging data or various other things, because there's so much to it and
there's lots in there.
But what I genuinely believe is that I've equipped you with all of the foundational knowledge you need.
The docs are great, and if you want to do something like a loop and you need to know how to do it,
you can just look in their docs.
And now you know the terminology.
You know about nodes.
You know about about things like an if and you know about how to use credentials of different sorts,
you should be able to pick up anything that's missing for you as you want, because this needs to cater
to many different audiences.
Nan is very, very broad and can go in different directions, but I hope that I've equipped you with
not just foundational knowledge, but quite advanced knowledge with a heavy leaning towards the AI.
Stuff like context engineering and MCP should be enough to really give you a good footing however you
want to continue your journey.
And that is why I can confidently say that at this point, you have earned your black belt.
You are a black belt and you can wear it with pride.
That doesn't mean it's the end of your journey.
There's still like the first and second and third down.
Whatever.
You can keep learning, keep building, make more and more advanced things, but recognize that you
are now an expert, you know, and you can build things with real, measurable business impact for yourself
and for your clients and for your agency, and you should start doing it today.
And it just remains for me to thank you so much for being part of this entire journey, coming all the
way to the end, even to this thank you segment, and I really appreciate it.
Remember, whether you like it or not, you get me with the package and I'm always available.
Please do connect with me on LinkedIn.
That's the link.
You can see it there.
I'm sure I've put it all over the resources because I tend to be very eager with this, but please do
that.
Post your certificate on on LinkedIn should you wish, and if you tag me, then I will come in and amplify
it as a way to sort of bring recognition to the fact that you've built up your expertise.
And maybe that's something that might attract the interest of perhaps a future client, a future agency,
a future employer, people who are on the look for experts or agent and voice agent experts, because
you are now one of them.
And my editor would kill me if I didn't mention that.
To the extent you're comfortable rating the course on Udemy, it makes a massive difference to how Udemy
recommends the course to others, so I would tremendously appreciate it if you did that.
As I say, makes a huge difference.
And if you're interested, if this course has piqued your interest in going a bit deeper and being more
technical, then you might want to check out my AI engineering courses.
There's one particularly on Agentic programming, which is something that might intrigue you.
So check it out, take a look if you want to go a bit deeper into this.
And the final thing I'll say.
Most important of all, the thing you've got to do, they must have, is that you have to go on out
there and build, build, build.
I hope that, if nothing else, what this course has shown you is that it is remarkably easy to make
substantial business impact in a very short amount of time, thanks to the power of Nan and 11 labs.
And that's exactly what you should go out and do.
And with that, thank you so very much.
One more time for sticking at it all the way till the very end.
I am super grateful, and I can't wait to hear about all the things that you build.