I want you to picture a hammer. It's sitting
there in a toolbox. It's a perfectly good tool,
sturdy, reliable, but it just sits there. It
does absolutely nothing until you walk over,
pick it up, and swing it. That is how I think
99 % of us are treating AI right now. We're treating
it like a hammer. Exactly. We use it when we
need it, then we put it away. But the dream...
The real dream we're all chasing, that isn't
the hammer, it's the construction worker. You
just tell the worker, build a wall right there,
you walk away, and when you come back, the job
is done. And that shift from the tool in the
box to the worker on the site, that is where
the economics of this whole thing just completely
change. Welcome back to the deep dive today.
We are exploring a really fascinating shift in
how we interact with this technology We're moving
beyond just chatting with a bot. We're talking
about setting up autonomous agents Specifically,
we're looking at a system called mole pot to
generate passive income. We're gonna be calm
practical and really try to get into the mechanics.
I am so excited for this one. And specifically,
the money part of it. Right. Because we've done
installation guides before, we've talked tech
stacks, but this is not about installing Python
just for the sake of it. This is purely about
the economics. How do you actually turn an autonomous
agent into an asset that works for you while
you sleep? Right. So let's map out where we're
going. We have a lot of ground to cover. We're
going to start with the philosophy of set and
forget what that really means, technically. Then
we'll look at building a service business, both
physical and in the cloud. And then we'll pivot
to digital products, so selling the skills themselves.
After that, direct income, like arbitrage and
content creation. And finally, and this is so
crucial, we'll break down a specific three -week
execution plan. because the source material is
very clear about how to start without getting
overwhelmed. It really requires a different way
of thinking. I think the source describes it
as moving from the chat to the loop. Most people,
myself included, use AI like a calculator. Yeah,
it's active work. I type a question, I wait,
it gives me an answer. And you are the bottleneck
in that whole equation. If you stop typing, the
value stops. So the source introduces this concept
of the cron job. OK. Now, For anyone who hasn't
spent time in a terminal, that sounds like pure
jargon. Oh, but yeah, let's unpack that cron
job. Sounds intimidating. It sounds scary, but
it's actually really boring. A cron job is just
a simple instruction to the computer. Do this
thing at this time forever. So when I'm chatting
with chat GPT, I'm the trigger. Exactly. You
type, it answers. In this model, the time is
the trigger. So give me a concrete example. How
does this loop work in the real world? OK. So
instead of waking up and asking, hey, what's
new in crypto, you script a command. You tell
your bot every single morning at 8 AM, check
the top five crypto news sites, summarize the
trends, and post it to my Twitter account. And
once you hit Enter on that one command. You never
have to touch it again. That's the difference.
The bot wakes up at 8, does the work, and goes
back to sleep. It does that every single day.
You know. There's something kind of wonderful
about that, isn't there? Oh, absolutely. I mean,
just the idea that you can trigger a command
once, and it just ripples out into the future.
It's like infinite leverage. It's magic. You
do the work one time, and the machine just honors
that instruction forever. And it removes the
friction of starting. The machine doesn't need
coffee. It doesn't get distracted. It just runs
the schedule. So if we had to distill this down,
what's the fundamental difference between a tool
and an agent? A tool waits for you. An agent
acts for you 24 -7. OK, so that's the philosophy.
But let's talk about actually selling this. The
source outlines two paths for service business.
And the first one is called assistant in a box.
Right. I have to be honest. When I read this
part, I was a little skeptical. Oh, yeah. Why
is that? Well, it suggests you physically buy
a computer, like a Mac Mini. Right. You install
the agent, set up all the security, and then
you literally mail the computer to the client.
Uh -huh. And in the age of the cloud, setting
a physical box just feels backwards. Why would
we do that? It does sound counterintuitive, but
the source argues this isn't a technical problem
you're solving, it's a psychological one. What
do you mean? Think about the client. A small
business owner. They are drowning in admin work.
They've heard about AI, but they are terrified
of a black and white command line. They don't
want to see the code? They don't want to see
code. They don't want to log into some server
they don't understand. So the box is like a...
The security blanket. That's it. Exactly. It's
tangible. It sits on their desk. They see the
little light blinking. And if they get nervous,
they can physically unplug it from the wall.
That makes so much sense. That physical control
is what you're actually selling. Yes. So you
charge a setup fee, say, 1 ,500 to 2 ,500 bucks,
then a monthly maintenance fee. And the value
is massive, right? They just saved 20 hours a
week. Right. But obviously, That model doesn't
scale infinitely. You can't be mailing out a
thousand boxes. So that brings us to the second
model, the automated VA agency. This is for the
clients who don't care about the hardware. You
host the bots yourself on a cloud server, AWS,
Digital Ocean, whatever. You basically become
the landlord of the bots. And what are these
bots doing for people? The low level stuff. the
repetitive cognitive labor. Checking email drafts,
scanning calendars for conflicts, doing competitor
research. The source breaks down the math and
it's pretty compelling. Walk me through the margins
on that because cloud hosting, that sounds expensive.
It's surprisingly cheap. To run one bot on a
server might cost you 10, maybe 20 bucks a month.
Add another 30 for API fees? That's the cost
of the AI's thinking. So your total cost is about
$50. Roughly $50. And you charge the client $300
a month. So you're clearing $250 a month for
each client. Right. Get 10 clients, and that's
$2 ,500 in profit. And you're not doing the work.
The code is. OK. But devil's advocate here. Dealing
with clients is hard. Support tickets, phone
calls. My bot is acting weird. What if I don't
want to talk to humans? Then you pivot to digital
products. You build the app store for bots. And
this is where we get into selling skills. Now,
when the source says skill, they don't mean a
tutorial, they mean an actual file, right? Correct.
In this multbot ecosystem, a skill is just a
configuration file. It's the code that teaches
the AI a specific workflow. You build the brain,
you sell the brain. The source gives a couple
of great examples. One was the YouTube processor.
Yeah, this is a perfect entry -level example.
Think about content creators. They have video.
They need text. You write a skill that connects
to a YouTube downloader. The user drops in a
link, and the bot downloads the audio, transcribes
it, and then writes a whole blog post. And you
sell that file for what, like $29? Exactly. It's
a volume game. But then you have the high -value
skills, like the lead hunter. This one sounded
a little more... It is. It uses a tool called
Appify. And the workflow is something like, find
me 50 marketing managers in London. The bot goes
out, scrapes LinkedIn, pulls the data, and populates
a spreadsheet. That is a soul -crushing task
for a human. For a bot, it's nothing. You can
sell that for $99 easily. And then there's the
idea of prompt libraries. Selling mastery packs.
Things like act as a legal expert or act as a
senior copywriter. You create the prompt once,
you make sure it works, and you sell it a thousand
times. I have to admit something here. Okay.
I've tried this. I've tried to build these really
consistent prompts, and I still really wrestle
with what they call prompt drift. Ah, yes, the
drip. No, you get it working perfectly one day,
and then by Friday, I don't know, the model updates
something, and suddenly the legal tone sounds
like a pirate. It's way harder than it sounds.
It is. And that's actually where the value is.
If it were easy, you couldn't sell it. You are
selling the reliability of that configuration.
You're selling the guarantee that this prompt
works. Exactly. So what are you actually selling
with a skill or a prompt pack? You're selling
the configuration file, the instructions that
make the bot do a job without hallucinating.
Let's move to the third income bucket, direct
income. This is where we cut out the client entirely.
We're not selling the bot, we're not selling
the skill, we're sending the bot out into the
world to just bring back money. The automated
content machine and arbitrage. Exactly. Let's
start with the content machine. The source mentioned
a specific file type here that I thought was
fascinating. A sol .md file. Yeah, this is where
it gets really sci -fi. A sol file. It sounds
so poetic for a coding tutorial. It really does.
But technically, it's super simple. It's just
a text file where you paste your own best writing,
your emails, your blogs, whatever. The bot analyzes
that file to learn your syntax, your humor, your
style. So it's not just generating generic AI
content. It's wearing your skin. A little creepy,
but yes. It takes dry facts, say, from a Google
Trends search and rewrites them through the lens
of your soul .md file. That's how you can automate
a blog that people actually want to read. And
the revenue just comes from ads or affiliate
links on the site. Right. You're building a media
company where the reporters are robots, but they
all write just like you. The other method was
market arbitrage. Buying low, selling high. But
using AI for speed. The example they gave was
vintage cameras on eBay. OK. You tell the bot.
Check eBay every hour. If you see this specific
vintage camera listed for under $50, message
me on Telegram immediately. So you're just looking
for mispriced items? You're looking for mistakes.
Someone just wants to get rid of something. They
list it cheap. The bot sees it instantly. You
buy it for $50. You resell it for $150. And then
there's the finance side of it, using APIs to
track sentiment. Right. And obvious disclaimer
here. This is not financial advice. But the tech
lets you monitor, say, Twitter mentions of Bitcoin
ETF. If those mentions spike 50 % in an hour,
that's a signal. The bot can catch that signal
before the mainstream news even writes the headline.
So when it comes to arbitrage, what's the bot's
main advantage? Speed. It finds the deal before
a human can physically scroll down the page to
see it. We are going to take a very short break.
When we come back, we're going to walk through
the three -week plan to actually get all of this
up and running. Okay, we are back. We've covered
the what and the why. Now let's get into the
how. Because that gap between understanding a
concept and actually having a bot running can
be massive. It is. And the source lays out a
three -week plan that's really designed to bridge
that gap. So, week one. The setup phase. The
source mentions using a tool called warp. Why
warp? Why not just the standard terminal? This
is a huge tip for beginners. The standard terminal,
that black box with white text, it's unforgiving.
You make one typo, it just yells error at you.
It doesn't help. Right? Warp is an AI native
terminal. Meaning what? Exactly. Meaning if you
type a command and it fails, you can literally
right -click the error and ask warp, hey, what
did I do wrong? And it will often explain the
mistake and just write the correction for you.
Like a safety net. Exactly. So week one isn't
about making money. It's just about getting Moltbot
installed inside Warp and connecting it to Telegram.
Just connecting the pipes. Right. You send a
message on Telegram and your computer responds.
That's the only goal. It sounds small, but that
feedback loop, I text my computer, it texts back.
That's the hello world moment for this whole
thing. Once you have that trust, you move to
week two, the experiment. The source suggests
something low stakes, like checking your Gmail.
Why Gmail? Because the API is free and the pain
point is real. You can just ask the bot to scan
for urgent emails and summarize them for you.
And this is where the agent part kicks in, right?
You're not sitting there writing the code yourself.
No. And this is the hurdle people need to clear.
You're telling the agent, here is the documentation
for the Gmail API. Please write a script to check
my inbox. You are managing the coder, not doing
the coding. It builds your confidence. Once you
see it work, you realize, OK, this is actually
real. Exactly. And then in week three, you monetize.
You just pick your path. Service, product, or
direct. Let's talk about scaling this up. Because
one bot checking email is cool. But 100 bots?
Yeah. That's a business. And this is where virtual
scaling comes in. If you have a bot running a
cooking blog and it's making $100 a month, you
don't just stop there. You spin up 10 more bots.
One for cars, one for tech. One for gardening.
You just clone the worker. But, and this is a
really big but, You have to watch your costs.
The API fees. They can eat you alive if you're
not careful. OpenAI charges for every single
token. They do, which is why the source suggests
using local models. Instead of paying OpenAI,
you use a tool called a llama to run a model
like llama3 directly on your own computer. So
you're basically bringing the brain in -house.
Exactly. If your machine is powerful enough,
it's free. Your electricity bill goes up a little,
but your API bill is zero. It's the difference
between renting intelligence and owning it. The
source ends with a bit of a reality check. Calls
this semi -passive. Which is honest. You have
to build the machine first. You can't just wish
it into existence. And there's a warning here
too. Do not use this for spam. Right. Don't be
the person flooding inboxes or ruining the internet
with junk. Use it to create value. Research.
Deal finding. Curation. So for someone listening
who is feeling a bit intimidated by all this,
what's the actual barrier to entry here? It's
just the willingness to learn the basics of how
computers and APIs work. It's grit, not genius.
Let's bring this all together. The big idea.
We are looking at a fundamental shift in how
wealth is created. We are moving from a world
where we trade our time for money, which is linear
growth, to a world where we manage digital employees.
And the stack we've talked about gives you options.
You can be the agency, renting out bots to stressed
business owners. Or you can be the architect,
selling the instructions, the skills to other
users. Or you can be the trader, using bots to
find money in the margins of the market through
arbitrage. The common thread is that you are
no longer the one doing the heavy lifting. You're
the one who designs the workflow. It does leave
us with a lingering question, though. If we all
have these soul files, these digital versions
of ourselves working 24 -7, what happens to the
value of the original work? That's the paradox,
isn't it? As the bots get better at imitating
us, the only thing that will hold value is the
one thing they can't automate, the actual messy
offline human experience. The hammer can hit
the nail. but it can't decide which wall to build.
Precisely. So here's my challenge to you. Stop
treating AI like a novelty. Stop asking it to
write poems about your cat. The opportunity right
now is massive because most people are still
stuck in the chat phase. Don't wait until everyone
has a bot farm. Go build your worker. Thanks
for diving, DSS. See you next time.