Welcome to the deep dive. Have you ever looked
at your to -do list and just felt, well, like
you're stuck in Groundhog Day, copying and pasting,
checking one app, updating another. It's manual,
it's repetitive, and let's be honest, it's pretty
graining. It really is. So much time gets lost
there. Exactly. So what if you could literally
hire an army of tireless digital assistants powered
by AI working 2047 in the background? Imagine
how much time that would free up. time for the
truly strategic, creative, fulfilling work you
actually want to be doing. That's the dream,
right? Right. So today, our mission is to explore
how you can create your very own AI agents. We'll
use a platform called NEN, and you don't even
need to write code. Yeah, no coding needed. And
we want to understand the profound difference
these agents can actually make in your work,
maybe even your life. And what's truly transformative
here, I think, is that we're moving beyond just
asking AI questions, like you do with ChatGPT.
We're talking about building entire systems,
systems that operate autonomously. So by the
end of this deep dive, you'll not only get what
differentiates these AI agents, but you'll probably
have a few aha moments. Aha moments, nice. Yeah,
as we connect the dots on how you can scale your
cognitive output. exponentially. This isn't just
about saving an hour here or there, it's fundamentally
restructuring how you can operate. That distinction
is really key, isn't it? Because when most people
hear AI, they immediately think of tools like
chat GPT, or Claude, or Gemini. You pipe a punk,
you get a response, and that interaction, well,
it typically ends right there. But AI agents
are, as you said, a completely different beast.
So what's the biggest misconception we need to
clear up right away? What makes these agents
so fundamentally unique? That's a great question,
because it's a critical difference. Think of
AI agents more like your Digital employees. Digital
employees, okay. Unlike a simple prompt response
system, these digital employees possess some
truly remarkable capabilities. First, they can
reason. Reason. How so? Well, it means they don't
just follow a script. They can actually analyze
a complex problem, break it down into logical
sequential steps, and then execute those steps
to achieve a final goal. Oh, okay. It's like
giving them a mission and letting them figure
out the best path forward. So it's not just internal
logic then. You mentioned they also have tool
use. Exactly. Meaning they're not confined to
just one application. They can interact with
multiple apps simultaneously. Like what? We're
talking Google Docs, your CRM, that's your Customer
Relationship Management System, Slack, even internal
databases. They can pull information from one
place and use it in another. Okay, that's powerful.
And crucially, They exhibit autonomous decision
making. Meaning? Meaning you don't need to hand
hold them through every single step. You give
them an initial objective and they can decide
which tool to use and what action to perform
next. All on their own. So they adapt. They adapt
to the situation as it unfolds. And perhaps the
most impactful part for your everyday life, persistent
operation. Oh yeah, that's huge. They can work
continuously in the background. triggered by
events or schedules, 204 .7. So while you're
focused on high value work or even sleeping or
on vacation, they're still grinding away, making
progress for you. Exactly. To really make this
tangible, let's consider a common sales process.
Okay. Manually, you'd be checking emails for
new leads, right? Copying their info. Yeah, maybe
googling their company. Yeah, then opening your
CRM creating a contact right drafting a personalized
welcome email Setting a reminder to follow up.
It's a lot of clicks a lot of context switching
and mental overhead It really is it is now imagine
an AI agent handling that okay. How would that
look it detects a new lead email? Autonomously
researches the company online Analyzes that information
to draft an outreach email perfectly tailored
to their industry Wow sends the email creates
the contact in your CRM, and even schedules the
follow -up task. All without me lifting a finger.
Pretty much. That's a game changer. Yeah, no
kidding. And this is a really critical distinction
from, say, traditional automation tools like
Zapier or Make. Right. I use those. They're more
like, if this, then that. Exactly. So those platforms
are fantastic. For those, if A happens, then
do B rules. They follow instructions precisely.
Or they don't think. Right. They can't really
adapt if something unexpected occurs. AI agents,
in contrast, possess these reasoning capabilities.
They can handle complex, maybe ambiguous situations
and make intelligent decisions beyond simple
rule following. Just like a smart human assistant
would. Precisely. That makes perfect sense. Yeah.
So with that clarity on what AI agents are, Let's
look at the tools. How do we actually build them?
And that brings us to NEN. NEN, yeah. It's an
open source tool, visual interface. You literally
drag and drop these nodes like digital Lego bricks.
That's a great analogy. Digital Lego bricks.
You connect them to build your automation system.
OK. And what's really powerful about NEN is its
visual workflow builder. It lets you clearly
see the entire flow. Data, logic, everything.
Makes complex stuff much easier to design and
understand. And it connects to lots of things.
Yeah, massive connectivity. Supports over 400
different apps and services right out of the
box. Plus, you can connect to virtually any API
out there. Wow. And being open source is a huge
advantage, too. Gives you maximum freedom, no
vendor lock -in. And here's a big one for a lot
of people. The self -hosting option. Crucial.
You can install innateN on your own. server,
meaning all your data, all your workflows, they
stay private, completely secure. It's your data,
in your control, absolutely. Which makes it incredibly
versatile. I can see this being used by content
creators automating social media posts, video
descriptions. Totally. Or businesses handling
lid capture customer support. Even for personal
use, right? tracking goals, summarizing daily
news, maybe? Absolutely. The possibilities are
really wide open. Now, to power NEN and these
tireless digital employees, you need a robust
engine behind the scenes. Right. You need somewhere
to run it. And for those looking for a straightforward
way to get NEN online, especially when you're
just starting out, a virtual private server of
VPS is often the best route. We found Hostinger
provides a great solution for this. Makes it
surprisingly easy, even for beginners. Yeah,
they've streamlined it quite a bit. They offer
a simple one -click N8n installation. One click.
Nice. Yeah, you don't need to be a server expert.
You just select their pre -configured N8n option
during setup, and it pretty much handles the
rest. Okay, and we should mention all the specific
plan recommendations and detailed instructions.
Those are in our show notes. Definitely check
those out for the step -by -step. Absolutely.
And it's worth noting, it's generally much more
affordable than N8n's own cloud service, especially
if you start building more workflows so they
get more complex. Right. Cost matters. Plus,
you get superior performance with dedicated resources,
your complex workflows run smoothly, and like
we said, full control. It's your server, your
data, your security. Makes sense. All the login
details, IP address, that'll be in your hosting
or dashboard then. Exactly. OK, so. Anynion is
up and running on our Hostinger VPS. You're greeted
by its Canvas interface, ready to build. Let's
walk through building a practical AI agent. Let's
do it. A great example is a comprehensive YouTube
content system. OK, what would that do? This
system would take a YouTube video URL and automatically
generate, say, multiple engaging titles, a detailed
description, SEO tags. Timestamps. Timestamps,
nice. Yeah, and even in an email newsletter announcing
the new video. Wow, okay, that covers a lot.
It does. This workflow basically functions like
a digital production line. It starts with a trigger,
usually a form where you paste the video URL.
Simple enough. Then comes data fetching. A node
retrieves the video's transcript. OK, it needs
the content. Right. Next, the AI brain, this
is where the magic happens, analyzes that transcript
and creates all the content. Titles, description,
tags, newsletter, everything. The heavy lifting.
Exactly. And finally, storage. It saves everything
neatly into, say, a Google Docs document. OK,
step by step. Step one, creating the trigger.
How do we do that? Easy. You just start a new
workflow on the N8n canvas. Give it a descriptive,
name -like YouTube content creation system. And
set up a form trigger. You give the form a title,
like enter YouTube video URL, add a field for
the URL itself. And remember to save your work
often. N8n doesn't autosave. Ah, good tip. Save
frequently. OK, step two, getting the video content,
the transcript. Right. For that, we use an HTTP
request node. This node lets NAN talk to pretty
much any web service. We'll connect it to an
external service, like a YouTube transcript or
API. You can find these on platforms like Rapid
API. Rapid API, what's that? Think of it like
an app store, but for software connections, for
APIs. Got it. You sign up there, subscribe to
a transcription API. Many have free tiers to
start. And then you paste your API key into the
credential section of the HTTP request node in
AEN. OK. Connect the API. And you configure the
node to pull the YouTube URL directly from the
form you just created in step one. Use a little
expression editor. It's quite intuitive. Right.
Connect the data flow. And a pro tip. Yeah. Always
execute and test each node right after setting
it up. Make sure you're getting the data back
that you expect before moving on. Test as you
go. Smart. Okay, now for step three, the AI brain,
the OpenAI integration. Yes, the core intelligence.
Every AI agent node in ANN typically has three
main components you might use. There's the chat
model, like OpenAI's GPT -40 or GPT -3 .5 turbo.
Okay, the engine. Then there's memory, which
is mainly useful for chat box so they can remember
the context of a conversation. We might not need
it much for this specific workflow. Right. And
then there are tools. These are actions the AI
can perform, like searching the web or, in our
case, creating documents. Got it. So how do we
set up the OpenAI part? First, you need an API
key from OpenAI. You get that from platform .openai
.com. Quick note. When you generate that key,
copy and save it somewhere secure immediately.
Why? Because they only show it to you once. For
security reasons. Oh, OK. Good to know. Copy
it right away. Yep. Then back in AI, you add
an AI agent node, choose OpenAI Chat Model as
the model, click Create New for Credentials,
give it a name like my OpenAI key, paste your
API key in there. It's straightforward. Then
you select your desired model. Maybe GPT -40
for the absolute best quality. Or you could use
GPT -3 .5 Turbo, which is much cheaper and still
very capable, especially if you're watching costs.
OK, choices depending on need and budget. Exactly.
And since we want the AI to save the content
it generates, we'll connect Google Docs as a
tool within that same AI agent node. Ah, OK,
the tool connection. Right. You click Add Tool.
select Google Docs, you'll need to create credentials
for Google too. Is that complicated? NEN actually
provides really clear step -by -step guidance
for setting this up in Google's developer portal.
It walks you right through it. Q, okay. Once
connected, you choose the append to a document
action. Then you just need the document ID. Where
do I get that? Just open the Google Doc you want
to use, look at the URL in your browser. It's
a long string of letters and numbers in the middle.
Copy that, paste it into the document ID field
in NEN. Okay, grab the ID from the URL. Got it.
And now for step four, which is arguably the
most important part. The prompt. Writing the
AI instructions. Comped engineering. The quality
of your AI agent's output depends entirely on
the clarity and specificity of your instructions
here. Like delegating to a real employee. Exactly.
The clearer the instructions, the better the
result. You want to build a structured prompt.
Give it a clear role first, like You are a digital
marketing mastermind specializing in YouTube
content. This kind of role -playing helps the
AI adopt the right tone and perspective. Okay,
set the stage. Then provide context. It will
receive a video transcript. Outline the request
in detail. Specify formats, like using Markdown
for easy copying. Ask for, say, five distinct
video title options. Much titles, okay. A full
video description, maybe specify needing a strong
hook, detailed content summary, timestamps extraction.
Oh, it can pull out timestamps. If you ask it
clearly and provide the transcript, yes. Often
it can identify key moments. And maybe a call
to action. Nice. Also ask for maybe 15, 20 optimized
SEO tags. A draft for a new video email newsletter.
Maybe even social media posts suggestions for
LinkedIn and TwitterX. Wow, that's a lot from
one prompt. It is. And crucially, you tell the
AI agent node to use the transcript data coming
in from the previous step, the HTTP request node,
as the input for this prompt. Use the expression
editor again to link that data. Feed the transcript
into the prompt. Okay, truly comprehensive. Finally,
step five. Test, refine, and activate. The moment
of truth. You click. Execute workflow, top right.
Then you open your form trigger, usually via
its test URL, paste in a real YouTube URL, and
hit submit. And watch any on end go. Yep. Watch
the nodes execute one by one. Yeah. Green means
success. Red means an error. What causes errors
usually? Often it's an incorrect data reference.
Maybe you pointed to the wrong data from a previous
node. Or the prompt might need tweaking if the
AI output isn't quite right. You just investigate
the node that failed, check its input and output
tabs. Debugging. Once you're happy with the output
in your Google Doc, you just toggle the active
switch on the workflow editor. And it's live.
It's live. Ready to run automatically every time
you submit a URL to that form. That's amazing.
What's so exciting about this system is that,
as you said, it feels like just the beginning.
Oh, absolutely. The true power of NAN lies in
its limitless scalability. This is just one workflow.
You can add more advanced features. Definitely.
You can add things like IF nodes or switch nodes.
These allow for smart splitting and routing of
your workflow. Example. Well... maybe based on
the video topic detected by the AI, you could
use a switch node to save content about Python
to a specific programming folder in Google Drive
and content about marketing to a different business
folder. Ah, intelligence sorting. That kind of
intelligence is fascinating. You could even build
a feedback loop. Imagine setting up another workflow.
This one runs, say, weekly. It pulls performance
data views, watch time, likes directly from the
YouTube API for the videos you process. And get
the stats back. Right. Then you feed that performance
data back into another AI agent node, and you
ask it. Based on these metrics, which titles
and topics performed best? Suggest five ideas
for the next video. Oh, continuous automated
improvement. Exactly. Yeah. That's when things
get really powerful. And the integration possibilities,
you mentioned over 400 apps. So you could automate
creating deals in your CRM. Like HubSpot. Yep.
Or post your AI -generated content directly to
LinkedIn or Twitter using their respective notes.
Add users to an email -nurturing sequence in
MailChimp. Sure can. Or create task cards in
Trello or Asana for your team based on the content
generated. It's like building an entire ecosystem
of digital assistants working together. That's
the idea. an interconnected system. Okay, now
when you're working with the data, especially
connecting all these services and using potentially
paid APIs, two critical things come to mind,
security and cost. Very important considerations,
absolutely. For security, number one rule, always
store your API keys and any other sensitive information
like passwords or tokens in NNN's built -in credential
store. Not directly in the workflow nodes? Never.
Never hard code them directly into your workflows.
The credential store encrypts them and keeps
them separate and safe. OK, use credentials.
Good practice. And as we discussed, self -hosting
NAN on your own VPS, like with Hostinger, is
a critical layer of security for your data itself.
It keeps everything fully within your control,
not on someone else's cloud. Right, data privacy.
And on the cost side, those OpenAI calls add
up, right? They can, especially with models like
GPT -4 .0. So... Optimize your prompts. Be concise
but clear. Get the output you need without unnecessary
length or back and forth if you can avoid it.
Makes sense. Shorter prompts, fewer tokens, lower
cost. Exactly. And consider using the cheaper
models, like GPT 3 .5 Turbo, for simpler tasks
that don't require deep reasoning or nuanced
creativity. Reserve the more expensive models
for where they really shine. Smart resource management.
OK. So if we kind of connect this all back to
the bigger picture, building these AI agents,
well, It might seem complex at first glance.
Yeah, looking at that workflow, it has a few
steps. But as you've seen, it's really about
connecting relatively simple building blocks,
those nodes, in intelligent ways. Like digital
Lego. Exactly. The key to success, honestly,
is to start small. Build one piece. Test it.
Add the next piece, test it. Incrementally. Yeah,
test every single step, and then gradually build
more complex systems as you get more comfortable
and proficient with the tool. That YouTube content
system we built today, it's just one example
then. Just one instance. With this foundational
knowledge, you truly can create AI agents to
handle nearly any repetitive process you can
think of in your work or life. It's leveraging
intelligence, not just basic automation. That's
the core difference, intelligence. So maybe we
should recap some golden rules for success for
someone listening who wants to try this. Yeah,
definitely. Golden rules. One, always start simple.
Expand gradually. Don't try to build Rome in
a day. Two, test each node independently as you
build. Seriously, this saves so much headache
later. Test, test, test. Three, invest time in
writing clear, detailed prompts. Prompt engineering
is absolutely crucial for getting good results
from the AI. Garbage in, garbage out still applies.
Right. Quality prompts matter. Four, always prioritize
security and privacy. Use the credential store.
Consider self -hosting for full control. Super
important. And five, don't be afraid to experiment
and innovate. The real magic happens when you
just start playing around, trying things out,
connecting different services. Okay, great rules.
So what does this all mean for you, the listener?
This isn't just about automation, is it? Not
at all. It feels like it's about gaining back
the most precious commodity we have. Time. Exactly.
Time for strategic thinking. Time for creativity.
Time for what truly matters to you. It's about
scaling your impact without necessarily scaling
your effort in the same way. Scaling impact without
scaling effort. I like that. And I truly believe
the future belongs not just to those who know
how to use AI. Like using chat GBT. Right. But
perhaps even more so. to those who know how to
build and direct it, how to orchestrate these
agents. By creating your own AI agents, you're
developing what I think is genuinely one of the
most valuable skills of the next decade. Building
and directing AI. Wow. So we really encourage
you. Pick just one tedious task, something you
do every day or every week that drains you. Break
it down into steps. Like we did with the sales
process example. Precisely. and then start building
your own little digital assistant in ADN to handle
it. See how quickly you can transform that part
of your workflow. Your first AI agent awaits.
It sounds achievable now. It really is. The tools
are ready, the instructions like we walk through
are pretty clear, and the possibilities seem
endless. They really are. And just a reminder,
you can find all the resources we mentioned,
the hosting or setup link, with that special
discount code, Aurelius, for 10 % off your first
order. It's all in our show notes. Yep, check
those out. And if you want to take your AI skills
even further, dive deeper. Check out the AI Fire
Academy Premium Plan. There's a 14 -day free
trial. What's in there? Instant access to over
500 pre -built AI workflows, advanced tutorials,
exclusive case studies. It's a great resource
to accelerate your learning. Fantastic. So really
it's time to dive in and unleash your own digital
workforce. Go build something cool.