Right now, while you're sleeping, a piece of
software is actually working. Yeah, it's not
just, you know, passively waiting for your next
command. It could be sending targeted emails.
It could be analyzing massive spreadsheets. Or
it could even be booking lucrative meetings.
It isn't just generating text anymore. It's taking
concrete action on your behalf. Intro music.
Exactly. It's stepping out of the chat box entirely.
Welcome back to the Deep Dive. It's genuinely
great to have you sitting here with us. Today
we're kind of slowing things down a little bit.
We're unpacking a really fascinating source document
today. It outlines seven specific AI business
ideas you can launch. And the truly wild part
about all this. You can start these businesses
with almost zero upfront money. Two secs silence.
Okay, let's unpack this because the entire digital
landscape is shifting incredibly rapidly today.
It really is shifting right under our feet. The
core thesis here is a massive paradigm shift.
We're finally moving away from basic generative
AI. That was the era of writing a simple text
prompt. You'd get text back. Right. And then
you manually copy paste it somewhere else. Exactly.
It was essentially just a really smart, autocomplete
function. Now we're fully entering the era of
agentic AI. We should definitely define that
term for clarity. Agentic AI takes action on
its own instead of just chatting. Yeah. It actually
does the clicking and typing for you. It logs
into websites and runs the entire process. It
navigates the software exactly like a human employee
would. The source text uses a really brilliant
analogy. here. It compares traditional software
tools to intelligent systems. A tool is basically
like a hammer in your garage. You still have
to physically pick it up and swing it. Right,
and if you stop swinging, the work completely
stops. But a system is a completely different
beast altogether. A system is a machine that
runs 24 -7. You basically build the machine one
single time up front. Then it operates continuously
without your daily manual input. It fundamentally
separates your personal time from your earning
potential. Two sec silence. So how do we actually
apply this? Let's examine the first concept from
our source material. It focuses on building a
highly automated local ad agency. We're targeting
local brick and mortar businesses. Like, you
know, car dealerships or local plumbers. Exactly.
Because they desperately need meta ads to survive
today. But they completely lack the technical
skills to run them. Historically, doing this
properly required a whole agency team. You needed
a specialized graphic designer for the creatives,
you needed a trained copywriter to draft the
text, and an account manager to handle the actual
client. It was a very expensive, clunky, and
slow -moving process. But today, you can build
an automated system instead. The document breaks
this down into four specific steps. First, you
create a strict brand guideline for the client.
You define their exact colors and their overall
vibe. Right. Then you upload that context into
Claude as a project. So it acts like a digital
brain with rules. Yeah. That customized context
window stays active forever. Step two involves
deep AI market research. The system scrapes the
Facebook ad library automatically. It analyzes
50 of their competitors' recent ads in minutes.
Step three is where the architecture gets really
fascinating. We connect directly to the dealership's
live inventory. You use a visual scraping tool
like Browse .ai. It visually identifies every
single used SUV currently in stock. It doesn't
require any complex coding to work properly,
which seamlessly leads right into step four.
the generation phase. The AI writes the copy
and generates the image. Then it directly logs
into MedEd's manager for you. It sets up the
entire campaign without manual clicks. The specific
prompt detail in the document is incredibly revealing.
You tell the agent to focus only on used SUVs.
You ask it to pull the top three financial offers.
Things like zero dollars down at signing for
new buyers. And you demand five human sounding,
engaging headlines. The final output ends up
being incredibly targeted. And the financial
business model here is just beautiful. You charge
a flat $1 ,000 to $2 ,000 monthly. That flat
fee is psychologically appealing to a local shop.
They absolutely crave predictable costs for their
marketing budgets. And for you, it's almost entirely
pure profit every month because the underlying
software costs are basically zero. It's a massive,
undeniable win for everyone involved. Let me
push back on the target audience just a bit.
Why specifically Target? tech lagging local businesses
for this service. Because the inherent value
gap there is absolutely massive. These older
shops are bleeding money by not being online.
Launching them into the digital space is huge.
The return on their monthly investment is completely
undeniable. So high impact for them means high
margins for you. That's the entire core of the
pricing strategy. Sussex silence. So that local
agency model fixes brick and mortar marketing.
But what if we pivot entirely to helping digital
workers? Let's examine the agentic sauce concept
from the source material. What's fascinating
here is how it flips traditional models. Usually
a sauce product just gives you a blank screen.
You log in, but you still do the work. Agentic
sauce actually executes the literal work for
you autonomously. It perfectly solves what the
author calls the upwork problem. Independent
freelancers waste countless hours doing unpaid
admin. They're endlessly scrolling through the
platform looking for work. They hunt for relevant
jobs and draft highly generic proposals. It's
an incredibly exhausting way to make a living.
But you can easily build a mini -agent to fix
this. You use tools like Cursor or Claude to
write Python scripts. But I have to make a vulnerable
admission here about coding. I still wrestle
with prompt drift myself on these projects. When
the AI slowly forgets your original core instructions,
getting Python code right the first time is really
tough. It takes genuine patience to build these
self -correcting scripts. Yeah, it definitely
requires some frustrating trial and error up
front. But once the script is finally running
smoothly, it's magic. This specific system checks
up work every 20 minutes without fail. It strictly
scans for new logo design jobs. Then it cross
-references the freelancer's actual past design
portfolio. It drafts a highly personalized, relevant
project proposal. Finally, it logs all the pitch
data into a Google Sheet. The freelancer just
wakes up and checks their daily spreadsheet.
They quickly review the drafted pitches and simply
hit send. It's basically a tireless personal
assistant that never sleeps. And the monetization
model is really clutter for this audience. You
don't sell them a recurring monthly subscription
fee. Instead, you sell them flexible batches
of automated credits. Right, like 100 automated
proposals for 30 bucks total. But why does the
credit pricing model work better than subscriptions?
Because freelancers absolutely hate taking on
fixed monthly financial overhead. Their project
income fluctuates wildly from month to month.
Credits feel like a direct, measurable investment
in their pipeline. If one $30 pack lands a job,
they're completely hooked. Lower financial risk
for them means faster product adoption. Yeah,
you completely remove the psychological friction
of buying software. Two sec silence. Here's where
it gets really interesting for larger scale operations.
What if a larger business relies entirely on
outbound sales? That brings us to the B2B sales
agency model. Oh, this specific outbound concept
is a total industry game changer. It completely
replaces the notoriously grueling job of an SDR.
Sales development reps historically have a very
rough time. Their whole job is manually sending
hundreds of generic LinkedIn messages. It's soul
-crushing work with notoriously high turnover
rates. But an AI agent obviously never gets tired.
You start by using data tools like Phantom Buster
or Clay. They intelligently daisy -chain different
corporate databases together behind the scenes.
You can pull a highly targeted verified lead
list in minutes. But blindly spanning people
doesn't work anymore. The real secret sauce here
is the deep contextual personalization. This
is truly the genius part of the entire system.
The AI agent actually reads the prospect's last
three LinkedIn posts. It systematically searches
for something highly specific and relevant. Usually,
it finds a nuanced point about AI or business
growth. The prompt engineering is incredibly
precise and careful here. You instruct the AI
to write a short two -sentence intro. It must
explicitly mention that specific point from their
post. Then it naturally asks for a casual 10
-minute workflow chat. People actually respond
to this because they feel genuinely seen. They
feel like someone actually took time to understand
them. It doesn't feel like a cold robotic copy
paste spam job. And the way you charge for this
is pure performance. You charge $100 to $200
per booked meeting. If your agent books 20 meetings,
that's $4 ,000. That's substantial monthly revenue
from just a single corporate client. And you
can easily run multiple client accounts simultaneously.
No, wait. Let's look at the actual output quality
here. Are the meetings actually high quality
if an AI booked them? Surprisingly, yes. They
actually are very high quality for sales teams.
The initial filtering with a tool like Clay is
extremely strict. Combined with highly relevant
outreach, the prospects are genuinely interested.
They show up to the call wanting to discuss a
real solution. Better filtering upfront creates
much better sales conversations later. Yeah,
you aren't just filling their calendar with useless
junk. Sponsor, mid -roll sponsor, read placeholder.
Two -sec silence. We're shifting away from outbound
sales into internal operations now. Let's deeply
examine the AI audits and the podcast agency
models. These two particular businesses are very
structurally different from each other, but they're
both incredibly lucrative if you execute them
well. Let's dive into the mechanics of the AI
audits first. An operational audit is essentially
just deep focused workplace observation. You
sit down and closely watch a company's teamwork.
You're actively hunting for the boring, highly
repetitive daily tasks. You look for painful
operational bottlenecks slowing everyone down.
Things like manually formatting meeting summaries
or answering basic client emails. You meticulously
identify exactly where the daily business friction
lives. Then you step in and install custom -clawed
skills for them. You train the AI agent directly
on their specific brand information. You feed
it their unique company voice and historical
email templates. The actual technical training
process usually only takes about an hour. But
the profound impact on their daily workplace
efficiency is massive, and your pricing model
definitely reflects that safe time. You typically
charge a $2 ,000 to $5 ,000 setup fee, plus you
add $500 a month for ongoing support. Because
technology changes incredibly fast, they desperately
need your maintenance. Now let's heavily contrast
that with the podcast agency model. This represents
a completely different approach to creating value.
The primary goal here is helping podcasters get
lucrative corporate sponsors. The source test
uses the AI Fire RSS podcast as an example. Your
automated system systematically scans platforms
like YouTube and Spotify. It actively looks for
channels with highly specific, valuable niche
audiences. It deeply researches their historical
view counts and overall engagement rates. Then
it emails marketing leads at relevant brands
to pitch. The prompt strategy for the sponsor
outreach is absolutely brilliant here. Imagine
you're pitching a niche show called Tech Talk
to a brand. You explicitly tell them about the
podcast's dedicated software engineer audience,
and you explicitly mention the show's impressive
10 % monthly growth rate. instantly becomes a
highly persuasive, purely data -driven sales
pitch. And the pricing structure here is based
purely on your performance. You take a flat 20
% success fee on any closed deal. If you land
a $10 ,000 sponsorship, you keep $2 ,000. These
two distinct models highlight the concept of
low -friction sales. The corporate audit business
requires a heavy upfront capital investment.
But the podcast agency is a pure risk -free performance
play. How do you intelligently balance running
these two different models together? You use
the upfront capital from corporate audits to
pay bills. Then you use the commission business
to build scalable wealth silently. It completely
removes your daily cash flow stress. Upfront
capital covers today while recurring commissions
build wealth tomorrow. Exactly. It's the perfect
financial safety net for a solo entrepreneur.
Two -sec silence. We're finally moving to the
last pairing of these business models. We're
looking closely at content repurposing and automated
real estate investing. Content repurposing is
an absolutely massive booming industry right
now. Digital creators are completely exhausted
from the constant endless content treadmill.
They desperately need a reliable system to recycle
their existing material. But the biggest most
common complaint in this space is always the
same. Generated AI text usually sounds like a
boring, soulless corporate robot. Right. To fix
this exact problem, you feed the agent 10 past
posts. The AI deeply studies these posts to establish
a mathematical style guide. It systematically
learns the creator's unique vocabulary and emotional
tone. Then it flawlessly rewrites their long
video transcripts into punchy text posts. For
platforms like LinkedIn specifically, the prompt
has strict formatting guardrails. You explicitly
tell it strictly no emojis and absolutely no
trendy hashtags. The pricing structure gives
the potential client two very different service
tiers. You charge $3 ,000 a month for the premium
high -end service. That premium tier includes
a human thoroughly checking the AI's generated
work. Or they pay $200 a month for a fully automated
feed. Most established, wealthy creators will
gladly pay the $3 ,000 fee. They desperately
want that human safety net protecting their fragile
brand reputation. Beat. Now let's pivot completely
into the traditional real estate market. This
specific application of agentic AI is genuinely
fascinating to me. The primary goal is finding
what professional investors call zombie properties.
These are highly distressed, ugly houses that
are sitting completely empty today. They're usually
owned by desperate people who must sell them
right now. In the past, investors literally drove
around local neighborhoods looking for these.
Now, the AI continuously scans complex public
property records in the background. It completely
automates the entire cold outreach process for
the investor. The AI sends a highly empathetic,
natural sounding text message to the owner. It
gently offers a quick cash, as is consultation
for the property. It deliberately positions the
message as coming from a helpful, concerned local
neighbor. The massive, unprecedented scale is
what makes this system work so incredibly well.
A dedicated human analyst might check 20 houses
in a single workday. Whoa. Imagine scaling to
analyzing 2 ,000 property histories in a single
afternoon. It completely changes the fundamental
financial math of real estate investing forever.
But how do you stop the AI from hallucinating
a bad offer over text? Well, the AI doesn't actually
negotiate the final cash offer with the seller.
It simply filters the massive property list for
initial seller interest and intent. You only
step in manually when the property owner finally
replies yes. Empathy at massive scale quickly
filters for genuine seller interest. Yeah, it
simply points you directly to the absolute warmest
leads available. Two sec silence. So what does
this all mean for us moving forward? We've covered
a truly tremendous amount of technical ground
here today. The ultimate most important takeaway
from this source document is surprisingly simple.
We're still standing in the extremely early days
of this technological shift. Most traditional
business owners are still heavily struggling
with basic email organization. You genuinely
do not need to be a world -class machine learning
expert. You really don't need an advanced computer
science degree for any of this. You only need
to be 10 % better than your target client. The
advanced technology inherently handles the actual
daily labor for you now. The AI systems do all
the tedious, repetitive, heavy lifting behind
the scenes. Your primary job is to be the strategic,
high -level architect. You simply design the
machine, and the machine autonomously does the
actual work. Beat. Start small. Build just one
agent today. Send one automated email sequence.
Once you finally see the system work just once,
it instantly clicks. The massive life -changing
potential of an agentic economy becomes incredibly
obvious immediately. That brings us directly
back to you, the listener tuning in today. Don't
overwhelm yourself and try to build all seven
of these businesses tomorrow. Pick just one specific
system from today's deep dive to explore. Start
exploring the tools and building your automated
architecture right now. The technical barriers
to entry have literally never been lower than
today. But right before we go, I want to leave
you with a thought. Eat. We talked about building
empathetic AI agents to text distressed homeowners
today. And we talked about AI agents pitching
corporate podcast sponsors completely automatically.
Millions of autonomous digital agents all waking
up to work every morning. So what happens to
the economy when your automated SDR agent pitches
another company? and it ends up pitching directly
to their automated AI gatekeeper agent instead.
Are we just building an internet where our machines
negotiate with each other while we sleep? Two
secs silence. Thanks for joining us on this deep
dive. We'll see you next time.