You know, when you look at the creator economy
right now, it really feels like the only way
to win is to be the loudest person in the room.
Oh, for sure. It's the attention economy. Everyone
is chasing viral fame, trying to be the next
big thing on TikTok, you know, filming themselves
in public, just desperate for that attention.
If you aren't visible, you don't exist. That's
kind of the rule. That's the common wisdom. Yeah.
But then you read a document like the one we're
covering today and you realize there's this.
This whole other group of people doing the exact
opposite. The quiet ones. They're anonymous.
They aren't winning literary awards. They're
not doing book tours. But they are quietly, you
know, sitting in the shadows, generating somewhere
between $800, $1 ,100 a day. Which is just a
staggering amount of income for a writer. It's
absolutely wild. Right. And they're not doing
it by writing the next, you know, great American
novel. They're doing it with these extremely
specific niche fiction books, things like Age
Gap Werewolf Romance. And they're using a workflow
that looks less like writing and, I mean, more
like industrial manufacturing. It really is.
It's the ultimate example of systems engineering
applied to creativity. It's not art in the traditional
sense. It's supply chain management. Welcome
back to the Deep Dive. Today we are unpacking
a fascinating guide called How to Write and Publish
an AI Novel on Amazon. By Maxa. And I want to
be clear right off the top, we're not here to
debate the ethics of AI art today. That's a whole
other deep dive. We're here to look at the system.
Because what really struck me about this source
is that it doesn't read like a creative writing
class. It reads like a technical manual for fulfilling
ultra -specific demand. That is the perfect way
to frame it. Most people think AI novel means
you just, you know, push a button and a book
pops out. Right. But this guy argues that if
you do that and just get garbage, the workflow
we're going to look at is a seven step process.
It involves market research with like data science
tools, architectural plotting so the AI doesn't
get confused and a very specific distribution
strategy. So let's make this out from it. We're
going to look at the economics first. Why? These
tiny little micro niches are printing money while
the big publishers just ignore them. Yeah. Then
we'll get into what they call the surgical workflow.
Using perplexity for research, Claude for drafting,
and a tool with the truly hilarious name for
the covers. Nano Banana Pro. I still can't quite
believe it's a real tool, but we'll get there.
And then finally, we'll talk about the context
cage and how to stop the AI from hallucinating
and, of course, the Amazon SEO game. Sounds like
a plan. Okay, so let's start with the money.
The source makes this distinction that I think
really explains everything. It contrasts the
traditional publishing model, you know, your
random house, your penguin, with this new AI
indie model. And it all just boils down to the
size of the audience you need to survive. It's
all about overhead. I mean, if you're a traditional
publisher, you've got offices, editors, marketing
teams, legal departments. Right. So for a book
to even be worth your time, it needs to sell
tens of thousands of copies. You need mass appeal.
You need the next Harry Potter. But mass appeal
is incredibly expensive to market because you're
competing with Netflix, Fortnite, everything.
And this model just flips that on its head. Completely.
This model relies on what the source calls niche
hunger. You don't need millions of readers. You
need a very small group of absolutely obsessed
readers. Obsessed. Yeah. The source lists these
examples that, I mean, they sound like jokes
to the average person. Mafia romance with neurodiverse
protagonists or cozy mystery specifically for
45 to 60 year olds. I genuinely laughed when
I read. Age gap werewolf romance. But the argument
is that these readers are like starved for content.
They are. I mean, if you love that specific subgenre,
you can't just walk into a Barnes and Noble and
find a whole shelf for it. You might find one
book a year if you're lucky. So when you go on
Amazon and you find an author who produces exactly
that flavor, you don't just buy one book. You
buy their entire back catalog. You subscribe
to their newsletter. The loyalty is just off
the charts compared to general fiction. It's
the long tail theory. Kind of turbocharged. And
the math in the document is pretty compelling.
They break down the unit economics. You price
a book at $2 .99. Which is the impulse buy price.
It's basically the price of a coffee. No one
thinks twice about it. Exactly. So in $2 .99,
you only need to sell about 50 copies a day to
generate, what, $5 ,000 to $7 ,000 a month? And
that's just one book. The strategy here isn't
to write one masterpiece. The source explicitly
talks about the four book series strategy. If
you launch four books in a series, they all act
as a funnel for each other. You can hit that
50 sales a day mark across the whole ecosystem.
The document claims this has an annual potential
of over $240 ,000. That is a top 1 % income for
being essentially a Pulp Fiction writer. And
just look at the cost. book can cost you anywhere
from a thousand to five thousand dollars just
to get it ready for print right editing cover
design all that all of it here your cost is the
subscription fee for claude and maybe mid -journey
20 maybe 40 bucks a month the barrier to entry
has just completely collapsed so it's not about
writing the next great gatsby at all it's about
feeding a very specific hunger exactly you're
moving from mass appeal to obsessed reliability
okay so if the barrier is zero Why isn't everyone
doing this? Or I guess, why is most AI fiction
so bad? Because most people skip the engineering
part. They just open up ChatGPT and say, write
me a book about a werewolf. And the AI writes
something generic and boring and just full of
plot holes. This workflow, it's all about constraints.
Let's get into that workflow then. So step one
is research. And this isn't just, you know, brainstorming
ideas. They're using data. to find what the source
calls content gaps yeah they're acting like data
scientists the guide recommends using perplexity
specifically in its pro search mode you are not
looking for what's popular okay if you search
popular romance books you'll just get crushed
by the competition you're looking for complaints
complaints you mean like bad reviews Sort of.
The prompt strategy is to search Reddit threads,
Goodreads reviews, forums, anywhere. Readers
are saying things like, I'm so tired of reading
X or why are there no books about Y? You're looking
for frustration. Frustration equals demand. That
is brilliant. You're literally finding the market
failure. Precisely. And once you find a potential
niche, let's just stick with our monster romance
example, you have to validate it. You go to Amazon,
find the top books in that weird little category
and check their bestseller rank. Or BSR. What
does that tell you? If those books are selling
50 plus copies a day, you've got a green light.
If they're selling zero, the niche is dead. Move
on. OK, so we found a hungry crowd. Now we have
to actually plot the story. And this is where
the guide brings in a concept they call reverse
thinking. This was one of the biggest takeaways
for me. It's so key. The rule is you must plot
the ending first before you write a single word
of chapter one. Why is the ending so critical
for an AI? because of something called prompt
drift it's the technical term for what happens
when an ai writes a long story it starts out
strong but by say chapter four it forgets the
main character's motivation by chapter 10 it
completely forgets a subplot you started in chapter
two the story just It wanders. It creates those
infamous hallucinations and plot holes. Massive
ones. So by deciding the ending for, I mean,
literally asking the AI to generate 10 satisfying
endings and then you just pick one, you create
a destination, you turn that ending into a PDF.
The source calls it ending reference dot PDF.
Now, every single time you ask the AI to write
a chapter, you are referencing that PDF. It acts
as an anchor for the whole project. It's like
a GPS. If you don't put in a destination, the
GPS just drives around aimlessly. But if you
lock in the destination, every turn is calculated
to get you there. That's a great analogy. The
AI is the car, but that PDF is the satellite
lock. So why is that PDF step so critical for
the AI? It acts as an anchor so the AI never,
ever forgets the destination. So we have the
ending. But we still need the middle, obviously.
The source calls this next phase the Bible. Yeah,
this is where you build your constraints. You
need two more PDFs. The first one is the character
profiles. Okay. And the source notes something
really specific here. Ask for detailed physical
descriptions. If you don't lock down that the
hero has a scar on his left cheek, the AI will
forget it or move it to the right cheek or just
remove it entirely three chapters later. Consistency
is really the enemy of large language models.
It really is. So you lock the characters in a
PDF, then you build the structure, and the source
swears by the save the cat method. Which is that
famous Hollywood screenwriting formula, right?
Exactly. Blake Snyder's beat sheet, it's got
15 beats. Opening image, theme stated, catalyst.
Dark Night of the Soul, Finale, all of it. Why
save the cat specifically? I mean, why not just
a standard three act structure? Because AI naturally
wants to resolve conflict. Have you ever noticed
that if you ask an AI to write a story, everyone
tends to get along a little too quickly? It tries
to be helpful and nice. Yes. Oh my god, yes.
It hates tension. It just wants everyone to go
have some tea and resolve their differences calmly.
Save the Cat forces tension. It forces a dark
night of the soul where the hero has to lose
everything. By forcing the AI to follow this
beat sheet, you stop the story from becoming
this boring sequence of nice events. So you upload
your ending PDF and your character PDF to Claude,
and you just say, create a chapter -by -chapter
outline using the Save the Cat structure. That's
the prompt. I love the analogy the source uses
here. It compares this to... To building a blueprint
before you lay a single brick. Most people just
want to start writing. But this workflow spends
a huge amount of time just building the constraints.
That's the key word right there. Constraints.
AI is creative, sure, but it's chaotic. You have
to fence it in. So we aren't writing yet. We
are just building constraints. Right. We're building
a context cage so the AI stays on track. I love
that term, context cage. It really implies the
AI is this wild. animal that needs to be penned
in so okay the cage is built now we actually
have to generate the pros now the fun starts
the source recommends using claude 4 .5 opus
in project mode let's walk through the actual
drafting phase because this is where the industrial
part really kicks in yeah this is the assembly
line you open a fresh chat you upload your three
holy grail pdfs and you start with chapter one
But, and this is really crucial nuance, you don't
just say write chapter two. You have to reprime
the pump every single time. How so? Your prompt
has to be something like write chapter two, aligning
closely with the save the cat structure and the
character profiles in the attached files. You
have to constantly remind it of the constraints.
If you stop reminding it, it starts to hallucinate.
And even with all of that, the source mentions
a very specific technical hurdle. The context
window limit. This is the bottleneck. Even the
best AI models, like Claude Opus, have a limit
on how much text they can hold in their active
memory. For a novel, you usually hit that wall
around chapter 15. And the AI starts to get dementia,
is how they put it. It forgets what happened
in chapter one. Right. I think we've all seen
that in long chat threads. The bot starts repeating
itself or contradicting itself. The source offers
a workaround for this that feels very... Manual.
It is manual, but it's effective. It's a hard
refresh. Once you hit that limit, say chapter
15, you take everything you've written so far,
compile it into a new PDF called chapters 1 to
15, and you start a brand new chat session. Oh,
wow. And you upload that new PDF as its history.
You're manually giving it a long -term memory.
You're giving it a summary of the past so it
can continue the future. It's like you're clearing
its cache. Yeah. And the speed difference. I
mean, the comparison between the free plan and
the pro plan was startling. The source says on
the pro plan, doing all this, you can finish
a full novel draft in a single afternoon. A single
afternoon. That is, I mean, honestly, it's hard
to wrap my head around that kind of volume. It's
industrial scale. It is. But I have to be vulnerable
here for a second. I still wrestle with prompt
drift myself, even with all these PDFs and context
cages. Sometimes the AI just... It goes off the
rails. It takes a lot of active management. You
aren't just watching Netflix while it writes.
You are reading every output, checking for drift,
regenerating scenes. It's not writing, but it
is intense editing. It sounds like memory management
is the real skill here. Yes. You're managing
the AI's short -term memory to maintain a long
-term narrative. We're going to take a quick
break, but when we come back, we need to talk
about the final polish, how to make sure this
doesn't sound like a robot wrote it, and the
tool called Nano Banana Pro that solves the biggest
problem with AI art. Stick around. Welcome back.
We're deep diving into the workflow of high -volume
AI authors. We've researched a niche using data.
We've plotted the ending first to avoid drift.
And we've generated a draft using a context cage
of PDFs. Right. But now we have a raw manuscript.
And let's be honest, raw AI text is usually pretty
dry. It's competent, but it's soulless. It tends
to overuse certain words like shiver, tapestry,
and delve. It really, really loves the word delve.
So how do we fix that? The source outlines a
two -phase editing process. Yeah. And phase one
is actually using AI against itself. Right. You
don't start by reading it yourself. You upload
the whole draft back into Cloud and you ask it
to look for logic errors. You say, identify continuity
errors. Did I say the door was locked and then
she walked through it? Did I change the car from
a Ford to a s***? Chevy. And AI is good at that.
Incredibly good. It spots those logical breaks
because it just treats them as data points. But
phase two. Phase two has to be human. Phase two
is the human Polish. This is where you actually
earn your money. You have to look for tone, voice,
and emotional rhythm. And the source suggests
a simple, brutal test. Read the first chapter
and the last chapter out loud. Out loud. Yep.
Your ear catches things, your eye misses. If
you trip over the words or if the dialogue sounds
like a robot trying to act human, the reader's
going to hate it. You have to make sure the emotional
beats are actually landing. If the dark night
of the soul doesn't make you feel something,
you have to rewrite it manually. Okay, let's
move on to the cover. We've all seen AI art.
It can be incredible, but it has a notorious
weakness. Hands are getting better. But text.
Oh, text usually looks like alien hieroglyphics.
It's a mess. It's like a soup of letters. A disaster.
But this guide recommends a tool I had never
even heard of. Nano Banana Pro. I know, right?
It sounds like a mobile game for toddlers. Nano
Banana Pro. It's actually a specific tool you
can access through the Gemini ecosystem. And
the source recommends it over mid -journey or
daily. Purely for text rendering. It can actually
spell the title correctly. It can spell. If you're
selling a book called The Werewolf Secret, you
cannot have the cover say The Werewolf Scrit.
Midjourney really struggles with that. Nano Banana
Pro handles typography inside the image generation
much better. And it handles the aspect ratio,
the book cover dimensions? Yes. The guide is
specific. 2560 by 1600. pixels the claim is that
you can generate a professional looking cover
with legible title text in about 15 minutes and
critically it's free that really is a moment
of wonder for me i remember when getting a cover
design cost 500 and took three weeks of back
and forth emails with a designer and now it's
15 minutes and zero dollars it's just wild it's
the democratization of the entire supply chain
it unlocks the ability for anyone to look professional
So why use Gemini or Nano Banana specifically
for the cover? It's the only one that doesn't
mess up the text on the book title. OK, so we
have the book. We have the cover. Now we have
to sell it. And the source says this is where
most authors fail. Great book plus bad SEO equals
no sales. This is where we have to change how
we think about Amazon. We tend to think of it
as a bookstore. You know, we imagine brising
shelves. But the source is very clear. Amazon
is a search engine. It's Google. But for products,
if you aren't optimizing for the algorithm, you
are invisible. So how did these authors optimize?
They use AI again. The workflow uses ChatGPT
specifically in its thinking mode to analyze
the market. You feed it your novel summary and
ask it to analyze successful book descriptions
in your specific niche. And then ask it to generate
titles. SEO optimized titles and subtitles. You're
not trying to be clever with your title. Right.
You know, The Moon's Glow is a poetic title.
Alpha Wolf's Forbidden Mate and Age Gap Romance
is an SEO title. You want the keywords that people
are actually typing into the search bar to be
right there in your title and subtitle. And then
there's the pricing strategy. The source is very,
very specific about the sweet spot. The golden
zone. It's $2 .99 to $9 .99. This is an Amazon
rule. If you price your book within that range,
Amazon gives you a 70 % royalty rate. If you
go below $2 .99, your royalty drops to 35%. And
if you go above $9 .99, it drops to 35%. Wow,
that's a massive cliff. It really forces your
hand. It forces the entire market into that pocket.
So almost every indie author sits right at $2
.99 to maximize their volume while keeping that
70 % cut. It's fascinating how the platform dictates
the economics, which then dictates the content.
Completely. You format it with Kindle Create,
which is a free tool from Amazon. You upload
it to KDP. And within one to three days, you're
live on the biggest bookstore on earth. So Amazon
is treated more like a search engine than a bookstore.
Precisely. You are optimizing for keywords, not
for browsing. It's incredible to see it all laid
out like this. When you zoom out and you look
at the research, the context cages, the nano
banana covers, it's... not really about writing
in the romantic sense of the word, is it? No,
not at all. If I had to summarize this whole
deep dive, I'd say this. It is not about art.
It's about pipeline management. It's a seven
-step industrial workflow. You have research
with perplexity to find the demand. You have
structure with Save the Cat to tame the chaos.
You have context management with those PDF cages
in Claude. And you have distribution via Amazon
SEO. It's just systems engineering applied to
imagination. Systems engineering applied to imagination.
That's a really powerful way to put it. The source
wraps up with a bottom line that I think is important.
It says, this isn't magic. It works for people
who think in systems and value volume over perfection.
It's for the person who's willing to put in the
reps. That's the truth of it. The barrier to
entry is low. Anyone can buy a subscription.
But the barrier to success is consistency. You
have to treat it like a job, not a hobby. As
we wrap up, I just want to leave you with a thought.
We talked about niche hunger today. Those readers
who are just desperate for something very specific
that they can't find. My question to you is,
what is the micro niche that you know better
than anyone else? What's the weird specific topic
that you and your friends complain there isn't
enough content about? because chances are there
are a few thousand other people thinking the
same thing, just waiting for someone to build
the system to feed them. That's the million -dollar
question, or at least the $240 ,000 question.
Thanks for listening to The Deep Dive. We'll
see you next time.