Most AI startups, well, the reality is they often
don't make it. They can burn through millions
of dollars, often for ideas, maybe prototypes
that aren't even finished. But what if there
was a different path, a kind of hidden blueprint
maybe, for building something actually profitable?
A business starting at maybe $12 ,000, $13 ,000
a month, but then scaling all the way to $5 million.
And the key is... profitable from day one. Exactly.
It's not just a concept. It's a genuine real
-world blueprint. And it completely flips that
traditional startup playbook, just turns it upside
down. It's really about building a business that
makes sense from the get -go. Welcome, everyone,
to The Deep Dive. Today, we're digging into this
model called the leveraged agency. It's a fascinating
approach. Seems really practical, not just another
buzzword. It's a guide for building an AI business
that's actually... highly profitable. And the
core idea, it seems to be about focusing on real
customer problems first, not just chasing the
shiniest new tech because it's cool. That's absolutely
it. And we're going to walk you through the whole
journey today. We'll unpack the three main phases,
right? Starting with that manual foundation,
then the AI transformation bit, and finally,
how you scale it up with different tiers. Plus,
we'll get into some really crucial stuff like
why building in public is so powerful and how
to avoid the common traps, you know, the ones
that trip people up. It really does sound like
a fundamental shift. OK, let's unpack this. So
when we think about AI startups, usually the
picture is, well, I call it the Silicon Valley
mirage. You know, you imagine these secret labs,
right? Founders trying to raise massive VC rounds,
burning cash for years, maybe chasing some unicorn
idea. It feels like this huge gamble. And honestly,
like. 90 % just fail. And even the ones that
succeed, the founders often end up with just
a tiny slice of the pie after all that dilution.
It's tough. Oh, completely. That old way. For
a lot of founders, it's just broken. This leveraged
agency model is, well, it's a smarter path, more
sustainable. It's not about building some cool
new hammer and then desperately looking for a
nail. No, it's about finding someone with a real
headache, a persistent, annoying problem. And
then you carefully, methodically create the perfect
aspirin for that specific pain. that framing
really helps clarify it so the core philosophy
is genuinely customers first ai second you don't
just jump into coding some complex ai hoping
someone wants it instead you start with the customer
find their most painful maybe boring everyday
problem then you actually roll up your sleeves
solve it manually first that way you learn everything
right all the little details the edge cases then
only then do you bring in ai build a system to
deliver that same solution just Better, faster,
more profitably. So the AI isn't the product
itself. It's more like the delivery system, a
really efficient one. And this whole approach
gives you like five huge, almost unfair advantages.
First. Profitable from month one. Seriously.
You get paid to learn, making real money, solving
real problems. Second, you get real customer
validation. You're working with paying clients
so you know for sure you're building something
people actually need. Third, you keep your equity.
Own 100 % of your business. You build wealth
for you, not just VCs. Fourth, way less risk.
Your business is built on demand you've already
proven with your manual service. Cuts down the
failure chance big time. And fifth, scalable
power. The AI becomes this amazing force multiplier.
One person can do the work of a whole team. You
can handle way more clients with the same effort.
So it really changes the risk -reward calculation
for starting something new. Yeah, it means solving
actual problems pays off and fast, grounded in
reality. That makes perfect sense. So the core
takeaway here is getting paid to validate your
idea and build something the market actually
wants. Exactly. Paid validation, reduced risk,
keeps you in control. Okay, so moving into phase
one. The manual foundation. This feels, yeah,
really counterintuitive, especially if you come
from tech. The idea that for the first six months
you have to do the boring manual stuff yourself.
It's like building a skyscraper, right? You don't
start with the fancy windows. You start with
digging the foundation. It's dirty work, maybe
invisible, but absolutely essential. You have
to deeply understand the ground you're building
on the market, the client's real pain, the process
with all its messy bits. That foundation is everything
and your first job. Find the perfect boring task.
You're hunting for that soul -crushing work,
the repetitive stuff businesses hate doing and
will happily pay to offload. And it needs to
meet four criteria, okay? One, high pain point.
Nobody on the client's team wants to touch it.
Two, universal demand. Lots of businesses need
this done. Three, repetitive and rule -based,
so it's predictable, something you can automate
later. And four, clear deliverables, success
is obvious, easy to measure. And there are just
so many examples hiding right there, aren't there?
Things like managing complex insurance forms
or tedious invoice processing. Data entry. We're
managing online reviews, pulling data from PDFs
into Salesforce .complex customs paperwork. Even
just converting messy PDF bank statements into
clean Excel files. That's a good one. Extracting
key data from contracts, too. It's amazing how
much value is locked up in these everyday tasks.
Totally. And the execution plan for this phase,
it's pretty structured. Zero to a profitable
service. Step one is the setup. Takes maybe a
week or two. You pick one boring task, create
a simple service package, maybe $500 to $2 ,000
a month. And here's the key. Sell the outcome,
not your time. They're buying clean data, not
your hours. Then months one to three, that's
the acquisition goal. Get your first five to
10 clients, real world validation. And as you
work, document everything, every single step,
every weird edge case, everything. Finally, my
three to six is the documentation. This is where
the real IP gets built. You become like a process
detective. You create a perfect battle -tested
standard operating procedure, an SOP, your blueprint,
honestly. That SOP is probably the most valuable
thing you build in this whole phase. And the
goals for phase one seem pretty clear. You're
aiming for, what, $1 ,000 to $5 ,000 in monthly
recurring revenue, MRR, plus five or more happy
clients, that perfect SOP, and profit margins
over 40%. Healthy numbers. Yeah, and a great
real -world example, there's this... Service.
Bank statement converter. Does one simple, boring
thing. Turns messy PDF bank statements into clean
Excel files. Solves a huge pain for accountants,
small businesses, super clear value. And that
simple service, reportedly doing over $40 ,000
a month in revenue. Wild, right? You know, I
still wrestle with prompt drift myself when trying
to automate some of these nuanced processes.
But having that meticulous SOP really does help
anchor things. So, OK, you've got the solid manual
foundation. You've got the SOP. The next logical
step is bringing in the AI. Exactly. That's how
you scale it. Automate that manual work. This
sounds incredibly disciplined starting manually.
What's the single biggest mistake people make
here before even touching AI? Probably automating
too early or picking a task that isn't really
that painful or repetitive for the client. Skipping
the homework. Right, so really resisting that
tech urge and doing the manual work first to
truly learn is critical. Don't automate too soon.
Okay, phase two, the transformation. Months,
say 7 to 12. This feels like where the real leverage
kicks in. You've got a profitable service run
by humans and that perfect SOP blueprint. Now
it's the industrial revolution for your business.
You start replacing the manual work with AI robots.
That's the perfect analogy. The AI integration
is all about building those robots. First, you
choose your tools. You assemble your AI team,
right? Maybe you specialize tools like conversational
AI agents for customer interactions or platforms
for complex data processing, data extraction.
You might use Claude or Cursor for some custom
code if needed. And then you need a central nervous
system, something like Zapier or NAN to connect
everything, make the workflows run. Then step
two. Teach the robots. You literally mirror your
SOPs using AI. You take your documented manual
steps and turn them into automated AI workflows.
Start with the most repetitive bits. But crucially,
and it's important, you maintain human oversight.
Quality control is key during the switch. You're
basically the manager of this new robot factory,
making sure everything's perfect, constant improvement.
And this is where the economics get really interesting.
The new economics. The power of automation. Let's
look at those numbers. Yeah, and here's the golden
rule. Keep your pricing the same. Don't lower
it just because AI is doing the work. Think about
it. Manual phase, maybe you have five clients
at $1 ,000 a month. That's $5 ,000 revenue. Maybe
40 % margin, so $2 ,000 profit. Okay, now the
AI phase. Your automated system can handle, say,
50 clients easily with the same effort, maybe
less. That's $50 ,000 in revenue. But now, because
AI does the heavy lifting, your margin jumps,
maybe 80 % or more. Suddenly, that's potentially
$40 ,000 in monthly profit. Massive difference.
And the key insight there is you're selling the
outcome, not the labor. Customers don't actually
care how you do it. They pay for consistent,
reliable results. As long as the quality stays
high or even improves, they're... happy. They're
not buying your time. Whoa. Okay. Imagine scaling
from five to 50 clients with basically the same
personal effort. That's like one person suddenly
becoming an entire department overnight. It's
just a totally different scale. Yeah. What's
really fascinating is your value to the customer
stays high, maybe even increases, but your cost
to deliver just plummets. That transformation
is huge. But what's the trickiest part of keeping
that human oversight effective as AI takes over
more tasks? Probably the continuous fine -tuning,
making absolutely sure the AI handles all the
weird edge cases just as reliably as your expert
human self did. Constant vigilance. So it's about
constant calibration, ensuring AI reliability
matches human expertise, especially on the tricky
parts. All right, phase three. You've perfected
your automated system for one task. Now it's
time to expand, right? Scale beyond that first
service. This is where you build it into a bigger
empire, maybe. Exactly. We call it the three
-tiered empire. It's about creating smart, diverse
revenue streams. So tier one, that's your Michelin
star service. High touch enterprise clients.
Think $5 ,000 to $25 ,000 a month. White glove
treatment, custom integrations, dedicated human
support. For the big guys, Fortune 500s. Then
tier two, the fast casual option. Self -serve
platform, much lower price, maybe $100 to $500
a month. Standard dashboard, automated onboarding,
email support only, built for volume, super scalable.
And tier three. Wholesale ingredients. Basically,
API access. Usage -based pricing, like $0 .10
to $1 per transaction. You let other developers
build your AI's capability right into their own
stuff. Pure tech play. And there's this underlying
compounding AI effect, too, which is pretty amazing.
Your core AI system gets smarter every month,
almost for free, right? Because the base models
underneath it, like GPT -5, Cloud 4 .1, they're
constantly improving. So your service gets better,
more capable, but your costs don't necessarily
go up. That's a huge advantage. Yeah. And this
whole tiered approach leads to... pretty clear
growth path a conservative forecast might look
like. End of year one, 25K MRR. End of year 1
.5, maybe 50K MRR. End of year two, hitting $100K
MRR. And by the end of year three, you could
be looking at $400K plus MRR. That's over a $5
million annual run rate. Solid growth. Which
brings us back to something you mentioned earlier,
building in public. This becomes absolutely critical
for growth at this stage. Like content creation
isn't just marketing anymore. It's the main way
you get customers. Your business is the content.
Think of it like a reality show about your business.
Your content is the weekly episode. You solve
one problem publicly, show exactly how you do
it step by step, transparently. That naturally
pulls people in. You need a mix, right? A content
matrix, daily jabs, short, valuable stuff, quick
tips, process breakdowns, behind -the -scenes
bits, and weekly right hooks, deeper dives, case
studies, client wins, maybe even transparent
revenue numbers. And that creates this powerful
flywheel effect. Your recurring revenue pays
for more content. which attracts more clients,
which generates more revenue. It feeds itself.
Yeah, if you connect the dots, the content isn't
just marketing on the side. It is the growth
engine. Building in public feels, well, pretty
exposed. What's the biggest benefit and maybe
the hardest part of doing that consistently?
Huge upside is trust. And you get amazing direct
feedback. The hard part, just the relentless
consistency it demands. day in day out got it
so it builds incredible trust and feedback loops
but requires serious daily commitment okay let's
talk end game the real long -term power here
seems to be becoming a multi -preneur not just
running one business but a whole portfolio absolutely
your first successful business that creates your
franchise blueprint You haven't just built a
business. You've built a repeatable system. You
now have a proven way to find opportunities,
the tech setup for deploying AI agents fast,
content systems that work, operational knowledge.
You've got the playbook. And with that playbook,
you can basically launch new franchises in totally
different areas, creating multiple income streams,
the plan looks like. Year one, master one task,
scale it to $50 plus MRR. Year two. Launch number
two in a different vertical. Aim for combined
$100K plus MRR. Year three and beyond, add a
third, maybe even acquire small manual agencies
and plug them into your AI system. Goal, maybe
$500K plus in combined annual profit across the
portfolio. That's serious. And this model allows
for the dividend strategy, which is totally different
from VC -backed startups always reinvesting.
Here, you're profitable from month one, so you
have options. Pay yourself real dividends, improve
your lifestyle, fund new ventures from profits,
keeping 100 % equity, maintain flexibility, avoid
that crazy growth at all cost pressure, and it
diversifies your risk across different businesses.
Makes sense. And practically, the tech stack
involves things like workflow automation tools,
Gumloop, Zapier, Make, plus AI like Claw, GBT4,
business... infrastructure like Airtable, Stripe,
Intercom, Notion, and maybe no -code, low -code
tools like Bubble, Webflow, Retool for building
things out. Exactly. And for finding those initial
boring Tasks. Market research is key. Digging
into Reddit, Facebook groups, LinkedIn. Looking
for where people are complaining loudly about
tedious work. Remember the criteria. High pain,
big market, repetitive, clear outcome. Find that
universal groan. And like any good system, there
are ways to mess it up. The operator's manual,
the five cardinal sins to avoid. Yep. Got to
watch out for these. One, choosing tasks that
are too complex right at the start. Keep it simple.
Two, automating too early. Cannot stress this
enough. Do it manually first. Learn inside out.
Three, raising prices just because you automated.
No. Keep prices stable. Take the profit margin
win. Four, neglecting content. It's not optional.
Got to commit daily. It's your growth engine.
And five, trying to be everything to everyone.
Master one task, one industry first. Focus. Don't
spread thin. What really stands out about this
whole model is just how clear the roadmap is.
It feels tangible, executable. Of those five
sins, if someone could only avoid one, which
is the absolute killer for this model. automating
too early definitely it completely undermines
your understanding and your validation right
from the start fatal mistake so that foundational
manual work is truly non -negotiable rushing
automation just breaks the whole thing okay let's
recap the big idea here this leveraged agency
model it really is a blueprint for immediate
profit and scalable ai growth it flips the usual
startup script completely start with real customer
pain Solve it manually to learn deeply, then
automate for huge margins and keep all your equity.
It's all about delivering reliable outcomes.
Yeah, it honestly beats the traditional model
on speed, capital needed, and especially risk.
Your real competitive edge isn't just the tech,
it's the data you gather, the process expertise
you build, and the authority that comes from
sharing it all through content. You know, Sam
Altman talks about the era of the idea guy, this
model. It shows you how to actually execute those
ideas profitably, practically. And the window
of opportunity for these AI services, it feels
wide open right now. The tools are there, they're
powerful, but most businesses, big or small,
they just... haven't figured out how to use them
effectively yet and that gap yeah that gap right
there that's your opportunity so maybe a final
thought for everyone listening what's that soul
-crushing tedious task you know businesses hate
doing what could you tackle first thank you so
much for joining us on this deep dive yeah i
hope you found some valuable nuggets in there
until next time out tiro music