The build
January to February: from my first Claude Code session to a working SaaS. I include the prompting rhythm, breakdowns, and shortcuts worth keeping.
The $19 Playbook. One real month, with the bad calls left in.
I built a SaaS with AI. Four months later, Meta attributed $102,431.19 in revenue to its ads.
This is the month written down: the build, the first $57.19 ad, the rules I used to manage the budget, and the costs behind the headline.
One payment. Instant access. 30-day refund. Read the result notes.
A month of decisions, written down.
The Playbook explains what I chose, what happened next, and what I would change if I started again.
The first ad
How the offer became an ad, why the first $57.19 mattered, and what the account had to learn before I spent more.
The money rules
The guardrails I wrote before launch: when I stopped an ad, when I waited, and when I increased the budget.
The $100K month
April, decision by decision: what scaled, what stopped, and how Meta came to attribute $102,431.19 in revenue.
The honest math
Revenue beside ad spend, with the limits of attribution in view. The result was not the same thing as net profit.
The routine
A plain-language way to turn your own idea into a measurable test, without copying my product.
January to April
The slow part belongs in the story too.
Most of these four months were spent learning, fixing things, and making small decisions.
Learn
I opened Claude Code for the first time and learned by building.
Ship
The SaaS became a working product built with AI assistance.
Test
The first Meta ad went live with $57.19.
Spend more
$26,489.59 in ads; $102,431.19 attributed back; 818 customers recorded.
Speed did not remove judgment. It gave judgment more chances to meet reality.
From the Playbook
A page from the Playbook
The screenshot isn't the lesson.
The useful part is everything that came before it: making the first version, choosing the first bet, and deciding what to do with uncertain data.
It is written for builders and marketers who want to inspect the process and adapt it to their own work.
Dear reader,
In January I did not know how to code this. In March the ad account did not know who would buy it. Those were not disadvantages to hide; they were the starting conditions.
The product got built because every vague idea had to become a specific instruction. The ads improved because every confident opinion eventually had to become a number.
AI shortened the distance between idea and evidence. It did not make evidence optional.
That is the system in this book.
A practical routine for your own project.
These five habits connect the build and the ads. The book shows how I used them in the real account.
Turn the idea into a testable brief
Define the person, pain, promise, and proof before asking AI to produce anything.
Build in short loops
Ask for one visible outcome, inspect it, correct the context, and then continue.
Write the money rules first
Decide what earns more budget and what ends a test before the numbers start changing your mind.
Keep the idea beside the metric
Track why each ad exists, so the next version has a reason behind it.
Close the week in writing
Record what happened, what you think it means, and what you will change next.
Read the finished month, or watch the next one happen.
Written Playbook, one-time payment
The $100K Playbook
$19 once
The full written record of the AI build and the first serious month of Meta ads.
- All six enclosures
- AI build workflow and ad process
- Money rules, mistakes, and decision logic
- Revenue, spend, and attribution context
- Instant access and yours to keep
30-day refund, no questions asked
Live account, monthly membership
The Cockpit
$99 / month · founding series
A numbered seat where the next decisions are visible before their results exist.
- Watch roughly $30,000/month in real ads
- See the plan, discussion, and verdict
- Vote on what deserves the next test
- Read the $7,000 Sunday ledger
- Founding price while membership stays active
For marketers managing $5K+/month in ad spend
A useful distinction: the Playbook is for learning the system from a completed month. The Cockpit is for qualified marketers who want to observe and influence an active one. Neither is a promise that your result will match mine.
Questions before you buy.
Is this a video course?
No. It is a written, practical decision record designed to be read and referenced. The focus is one real build-and-ad journey, not a library of generic lessons.
Was the $102,431.19 profit?
No. It was revenue attributed by Meta's tracking pixel. The page shows $26,489.59 in ad spend, but that still does not turn attributed revenue into net profit. The policy page explains the measurement language.
Do I need to know how to code?
No. The story starts with a first Claude Code session. You do need patience, clear thinking, and a willingness to inspect what AI produces rather than accepting it blindly.
Will the same ads and prompts work for me?
No one can honestly promise that. The reusable part is the workflow: clearer briefs, smaller tests, pre-written rules, and documented decisions. Your market still gets the final vote.
What do I receive for $19?
Instant access to the complete written Playbook, including the six enclosures described above. It is a one-time purchase, not a subscription.
What is the refund policy?
The Playbook carries a 30-day, no-questions refund. Contact Rana using the same email used for purchase. Full terms live on the policy page.
Why not name the SaaS publicly?
Because the case study should teach the operating system, not become another ad for the product. Cockpit members can see the account in context from the inside.
Read the month from the first decision.
The edits, wrong turns, money rules, and measurement notes are all left in.