https://preview.redd.it/ss9j142u3i2h1.png?width=1254&format=png&auto=webp&s=5a22342cabaa6c74afe06d647e3ac46cd3e448db

A lot of people think publishing ebooks is dead.

But I don’t think the opportunity is dead.

I think the problem is that most people publish the wrong type of books.

They create random books with no real search intent, no clear audience, and no reason for someone to buy.

If you want to make money with ebooks, the goal is not just to “write a book.”

The goal is to create a book that solves a specific problem people are already searching for.

That’s where passive income can start.

Not overnight.

Not guaranteed.

But if you publish the right books, in the right niches, with the right title and cover, they can keep selling after the work is done.

Here are some of the best niches I think are worth looking at:

1. Self-help

This is one of the strongest niches because people are always trying to improve their life.

Good angles are overthinking, discipline, confidence, habits, self-love, boundaries, focus, anxiety, and procrastination.

People don’t usually search for “self-help book.”

They search for a solution to a pain.

Example: how to stop overthinking, how to become disciplined, how to stop procrastinating, how to build confidence.

2. Money and personal finance

This niche is powerful because people buy books hoping to improve their financial situation.

Good angles are budgeting, saving money, beginner investing, money mindset, side hustles, financial discipline, and escaping bad spending habits.

The best books here are simple and beginner-friendly.

People don’t want complicated financial theory.

They want clear steps.

3. Business and online income

This works well because people want to learn how to make money online or start something on the side.

Good angles are freelancing, AI tools, digital marketing, selling online, productivity for entrepreneurs, and beginner business systems.

This niche can work well because the buyer sees the book as an investment.

4. Language learning

This is a very underrated niche.

People are always trying to learn English, Spanish, French, Italian, German, and other languages.

Good formats are short stories for beginners, travel phrasebooks, conversation practice, vocabulary builders, and grammar made simple.

The best angle is to target a specific audience.

For example: English for Italian speakers, Spanish for travelers, French short stories for beginners.

5. Health, fitness, and weight loss

This niche is always in demand.

Good angles are meal prep, walking plans, home workouts, high-protein recipes, weight loss for beginners, fitness after 40, and simple healthy habits.

The key is to make it specific.

A generic “fitness book” is too broad.

A book for a specific person with a specific goal is much stronger.

6. Cooking and diet books

Cookbooks can still work, but generic recipe books are weak.

The best ones combine food with a clear outcome.

Examples: healthy meals, cheap meals, high-protein recipes, air fryer recipes, Mediterranean diet, meal prep, beginner cooking, student meals.

People buy cookbooks when the promise is clear and practical.

7. Relationships and dating

This niche is strong because it connects to emotion.

Good angles are breakups, anxious attachment, dating confidence, self-respect, communication, toxic relationships, letting go, and rebuilding confidence after heartbreak.

Books in this niche can sell because people often buy when they are going through emotional pain.

8. Kids books

Kids books can work, especially if they have a clear theme.

Good angles are bedtime stories, confidence, kindness, emotional control, sharing, fear of the dark, school anxiety, and learning good habits.

Parents buy books that help their children learn something or feel something positive.

9. Journals and workbooks

This is good for KDP because workbooks and journals are simple to produce.

Good angles are gratitude journals, anxiety workbooks, habit trackers, goal planners, shadow work journals, manifestation journals, and self-care planners.

But the niche is competitive, so the cover and title need to be very specific.

10. AI and digital skills

This is a newer opportunity.

People want to learn how to use AI tools, ChatGPT, automation, prompts, and online productivity.

The best books are beginner-friendly and practical.

Not theory.

People want examples, templates, prompts, and step-by-step use cases.

The main lesson is this:

Don’t create a book around a broad topic.

Create a book around a specific search intent.

Bad idea:

“Self Help Guide”

Better idea:

“Stop Overthinking at Night”

Bad idea:

“Fitness Book”

Better idea:

“30-Day Walking Plan for Weight Loss”

Bad idea:

“Learn English”

Better idea:

“English Conversation for Italian Speakers”

The more specific the book is, the easier it is for someone to understand why they should buy it.

Publishing books can be passive income, but only after the active work is done:

Research the niche.
Create a strong title.
Make a good cover.
Write useful content.
Optimize the description.
Publish consistently.
Test what sells.

It’s not magic.

But it is a real digital asset model.

One book probably won’t make you rich.

But a portfolio of useful books in strong niches can become a long-term passive income stream.

The opportunity is not in publishing random books.

The opportunity is in publishing books people are already searching for.

https://preview.redd.it/xtsvlhkckzzg1.png?width=1448&format=png&auto=webp&s=6082bbbc1de0fa37722877455b44f88d0ba2da6c

A few months ago, I started a brand new Amazon KDP account.

No audience.
No email list.
No old books helping the account.
Nothing.

I wanted to see if I could use AI as part of the workflow and slowly build a catalog of books that actually sells.

So far, I’ve published 109 books.

The account recently passed around $1,100/month in royalties.

Sounds good, but honestly, it was not as smooth as that number makes it look.

A lot of the books did almost nothing.

Some barely sold.
Some broke even.
Some were probably a waste of time.
A few did way better than I expected.

That was probably the biggest lesson for me.

KDP is not really about finding one “perfect” book idea.

It is more about testing, learning, and slowly getting better at spotting what people actually want to buy.

AI helped a lot, but not in the way most people think.

It helped me move faster with things like:

• niche ideas
• outlines
• book structure
• descriptions
• keyword research
• editing
• formatting

But AI did not magically make the books sell.

The hard part was still the same:

Figuring out what people actually want.

Before I publish a book now, I usually look at things like:

• are people already buying books in this niche?
• is page one full of strong competitors, or are there weak spots?
• are the covers good or kind of average?
• can I make something clearer, more useful, or better organized?
• does the price/royalty make sense?
• would ads even have a chance of being profitable?

Early on, I made the mistake of thinking that publishing more books would automatically mean more money.

It does not.

Publishing more bad books just gives you more bad books.

The niche matters.
The title matters.
The cover matters.
The product page matters.
The actual usefulness of the book matters.

I also stayed away from fiction.

Maybe some people can make AI fiction work, but personally I think it is much harder to make it feel legit.

With fiction, readers care a lot about voice, emotion, pacing, characters, originality, and style. AI writing can feel flat very quickly there.

So I focused more on nonfiction.

Things like:

• self-help
• personal development
• productivity
• beginner guides
• practical educational books
• simple problem-solving books

For nonfiction, the value is often more about making the information clear, useful, and easy to follow.

AI can help a lot with that, but you still have to edit, organize, check the content, and make sure the book is actually worth buying.

Another big lesson:

Revenue is not profit.

A book can make royalties and still not be that profitable if ads are too expensive or the margin is too low.

So I started tracking more seriously:

• royalties
• ad spend
• profit per book
• click-through rate
• conversion rate
• organic sales
• which niches had repeat demand

Ads helped, but not because they magically made everything sell.

They mostly showed me what was broken.

If people saw the book but did not click, the cover or title was probably the issue.

If people clicked but did not buy, then the price, product page, reviews, or book idea probably needed work.

That feedback helped me improve faster.

Another thing people do not talk about enough is that the process takes time to build.

At the beginning, everything is slow.

Researching niches is slow.
Making covers is slow.
Formatting is slow.
Uploading is slow.
Writing descriptions is slow.
Testing ads is slow.

But after doing it enough times, you start building your own system.

You make templates.
You reuse workflows.
You get faster at research.
You start spotting bad niches earlier.
You get better at covers and titles.
You learn what not to waste time on.

Once the process is organized, I honestly think someone focused can create 2–3 decent nonfiction books per week.

Not masterpieces.
Not guaranteed bestsellers.
But real, useful, publishable books that can bring in some income over time.

The key is not just “use AI and upload as fast as possible.”

That is probably the fastest way to publish a bunch of books nobody wants.

The better approach is:

Use AI to speed up the boring parts, but still use your own judgment for the important parts.

My current view is that Amazon KDP is simple, but not easy.

The simple version is:

You create a book.
You publish it on Amazon.
Amazon handles printing and shipping.
You get royalties when it sells.

But the hard part is everything around that:

Choosing the niche.
Making something useful.
Creating a good cover.
Writing a title people understand.
Testing ads without burning money.
Improving based on the data.

AI makes the process faster, but it does not replace taste, judgment, or basic market research.

If anything, AI makes it easier to publish too much too quickly.

After 109 books, my biggest takeaway is this:

One book is a gamble.
A catalog gives you data.

But the catalog only helps if you actually learn from it.

KDP is not passive at the beginning.

In the beginning, it is research, publishing, testing, fixing, and repeating.

The passive part only has a chance to come later, once you have books that are actually selling.

If people are interested, I can share more about the workflow I used for niche research, book structure, covers, formatting, ads, and how I organize the process without rushing low-quality books.

A few months ago, I started a brand new Amazon KDP account.

No audience.
No email list.
No old books helping the account.
Nothing.

I wanted to see if I could use AI as part of the workflow and slowly build a catalog of books that actually sells.

So far, I’ve published 109 books.

The account recently passed around $1,100/month in royalties.

Sounds good, but honestly, it was not as smooth as that number makes it look.

A lot of the books did almost nothing.

Some barely sold.
Some broke even.
Some were probably a waste of time.
A few did way better than I expected.

That was probably the biggest lesson for me.

KDP is not really about finding one “perfect” book idea.

It is more about testing, learning, and slowly getting better at spotting what people actually want to buy.

AI helped a lot, but not in the way most people think.

It helped me move faster with things like:

• niche ideas
• outlines
• book structure
• descriptions
• keyword research
• editing
• formatting

But AI did not magically make the books sell.

The hard part was still the same:

Figuring out what people actually want.

Before I publish a book now, I usually look at things like:

• are people already buying books in this niche?
• is page one full of strong competitors, or are there weak spots?
• are the covers good or kind of average?
• can I make something clearer, more useful, or better organized?
• does the price/royalty make sense?
• would ads even have a chance of being profitable?

Early on, I made the mistake of thinking that publishing more books would automatically mean more money.

It does not.

Publishing more bad books just gives you more bad books.

The niche matters.
The title matters.
The cover matters.
The product page matters.
The actual usefulness of the book matters.

I also stayed away from fiction.

Maybe some people can make AI fiction work, but personally I think it is much harder to make it feel legit.

With fiction, readers care a lot about voice, emotion, pacing, characters, originality, and style. AI writing can feel flat very quickly there.

So I focused more on nonfiction.

Things like:

• self-help
• personal development
• productivity
• beginner guides
• practical educational books
• simple problem-solving books

For nonfiction, the value is often more about making the information clear, useful, and easy to follow.

AI can help a lot with that, but you still have to edit, organize, check the content, and make sure the book is actually worth buying.

Another big lesson:

Revenue is not profit.

A book can make royalties and still not be that profitable if ads are too expensive or the margin is too low.

So I started tracking more seriously:

• royalties
• ad spend
• profit per book
• click-through rate
• conversion rate
• organic sales
• which niches had repeat demand

Ads helped, but not because they magically made everything sell.

They mostly showed me what was broken.

If people saw the book but did not click, the cover or title was probably the issue.

If people clicked but did not buy, then the price, product page, reviews, or book idea probably needed work.

That feedback helped me improve faster.

Another thing people do not talk about enough is that the process takes time to build.

At the beginning, everything is slow.

Researching niches is slow.
Making covers is slow.
Formatting is slow.
Uploading is slow.
Writing descriptions is slow.
Testing ads is slow.

But after doing it enough times, you start building your own system.

You make templates.
You reuse workflows.
You get faster at research.
You start spotting bad niches earlier.
You get better at covers and titles.
You learn what not to waste time on.

Once the process is organized, I honestly think someone focused can create 2–3 decent nonfiction books per week.

Not masterpieces.
Not guaranteed bestsellers.
But real, useful, publishable books that can bring in some income over time.

The key is not just “use AI and upload as fast as possible.”

That is probably the fastest way to publish a bunch of books nobody wants.

The better approach is:

Use AI to speed up the boring parts, but still use your own judgment for the important parts.

My current view is that Amazon KDP is simple, but not easy.

The simple version is:

You create a book.
You publish it on Amazon.
Amazon handles printing and shipping.
You get royalties when it sells.

But the hard part is everything around that:

Choosing the niche.
Making something useful.
Creating a good cover.
Writing a title people understand.
Testing ads without burning money.
Improving based on the data.

AI makes the process faster, but it does not replace taste, judgment, or basic market research.

If anything, AI makes it easier to publish too much too quickly.

After 109 books, my biggest takeaway is this:

One book is a gamble.
A catalog gives you data.

But the catalog only helps if you actually learn from it.

KDP is not passive at the beginning.

In the beginning, it is research, publishing, testing, fixing, and repeating.

The passive part only has a chance to come later, once you have books that are actually selling.

If people are interested, I can share more about the workflow I used for niche research, book structure, covers, formatting, ads, and how I organize the process without rushing low-quality books.

https://preview.redd.it/kwg6c9otczzg1.png?width=1448&format=png&auto=webp&s=2402f7c7ddc47e1bb7fd7e878877c88bae03d3c6

A few months ago, I started a brand new Amazon KDP account from zero.

No audience.
No existing catalog.
No previous momentum.

I wanted to test something simple:

Can you use AI as part of the workflow and actually build a small KDP catalog over time?

So far, I’ve published 109 books.

The account recently passed around $1,100/month in royalties, but I don’t want to make this sound easier than it is.

A lot of the books did not perform well.

Some barely sold.
Some broke even.
A few performed much better than expected.

That was probably the biggest lesson for me:

KDP is not about creating one perfect book.

It is more about building a system, testing ideas, and learning from the data.

AI helped me move faster with things like:

• niche ideas
• outlines
• book structure
• descriptions
• keyword research
• editing support
• formatting support

But AI did not solve the hardest part.

The hardest part is still figuring out what people actually want to buy.

Before publishing a book now, I try to check:

• are people already buying in this niche?
• how strong is the competition?
• are the covers on page one good or weak?
• can I make something more useful than what is already there?
• does the price/royalty make sense?
• could ads realistically be profitable?

One mistake I made early was thinking that publishing more books would automatically mean more royalties.

It does not.

Publishing more bad books just gives you more bad data.

The niche, title, cover, product page, and actual usefulness of the book matter a lot.

I also decided not to focus on fiction.

In my opinion, fiction is much harder to do well with AI because it is easier for the writing to feel fake, generic, or not emotionally believable. Readers of fiction usually care a lot about voice, style, characters, pacing, and originality.

For me, nonfiction made more sense.

Things like:

• self-help
• personal development
• productivity
• simple guides
• beginner-friendly educational books
• practical problem-solving books

With nonfiction, the value is often more about structure, clarity, usefulness, and solving a specific problem. AI can help a lot with that, as long as you still edit, organize, fact-check, and make the book actually useful.

Another thing I learned is that revenue is not the same as profit.

A book can generate royalties, but if ads are too expensive or the margin is too low, the real profit can be much smaller than it looks.

So I started tracking:

• royalties
• ad spend
• profit per book
• click-through rate
• conversion rate
• organic sales
• which niches showed repeat demand

Ads were useful, but not because they magically made books sell.

They showed me what was broken.

If people saw the book but did not click, the cover or title was probably the issue.

If people clicked but did not buy, the product page, price, reviews, or book concept probably needed work.

That helped me improve faster.

The other thing people underestimate is that the process takes time to automate.

At the beginning, everything feels slow.

Researching niches takes time.
Making covers takes time.
Formatting takes time.
Uploading takes time.
Writing descriptions takes time.
Testing ads takes time.

But after doing it over and over, you start building your own system.

You create templates.
You reuse workflows.
You get faster at spotting weak niches.
You get better at covers and titles.
You learn what to avoid.

Once the process is organized, I honestly think anyone with some focus and consistent work can create 2–3 decent nonfiction books per week.

Not perfect books.
Not guaranteed bestsellers.
But real, useful, publishable books that have a chance to make some income over time.

The key is not just “use AI and publish fast.”

That is how you end up with low-quality books that do not sell.

The real key is:

Use AI to move faster, but use your own judgment to decide what is worth publishing.

My current view is that Amazon KDP is simple, but not easy.

The simple version is:

You create a book.
You publish it on Amazon.
Amazon handles printing and shipping.
You earn royalties when it sells.

The difficult part is everything before and after publishing:

Choosing the niche.
Creating something useful.
Making a good cover.
Writing a clear title.
Testing ads carefully.
Improving based on data.

AI can speed up parts of the process, but it does not replace judgment.

If anything, AI makes it easier to publish quickly, which also means it is easier to publish low-quality books quickly.

After 109 books, my main takeaway is this:

One book is a gamble.
A catalog gives you more data.

But the catalog only helps if you keep improving the process.

KDP is not passive at the beginning.

At the start, it is research, publishing, testing, fixing, and learning.

The passive part only has a chance to happen later, after you have built something that actually sells.

If people are interested, I can share more about the workflow I used for niche research, book structure, formatting, covers, ads, and how I organize the process to publish consistently without rushing low-quality books.

https://preview.redd.it/19jcyzy8lrzg1.png?width=1448&format=png&auto=webp&s=388e9be0e40303aed54dbd7852f53a14dc6e0905

A few months ago, I started a new Amazon KDP account from zero.

No audience.
No existing catalog.
No previous momentum on that account.

I wanted to test whether it was possible to use AI as part of the workflow and build a small catalog of books over time.

So far, I’ve published 109 books.

The account recently passed around $1,100 in monthly royalties, but I don’t want to make this sound easier than it is.

A lot of the books did not perform well.

Some barely sold.
Some broke even.
A few performed much better than expected.

That was probably the biggest lesson for me:

KDP is not about one perfect book.

It is more about building a system, testing ideas, and learning from the data.

AI helped me move faster, especially with:

niche ideas

outlines

book structure

descriptions

keyword research

editing support

formatting support

But AI did not solve the hardest part.

The hardest part is still figuring out what people actually want to buy.

Before publishing a book, I now try to look at:

whether people are already buying in that niche

how strong the competition is

whether the covers on page one are weak or strong

whether I can create something more useful

whether the price and royalty make sense

whether ads could realistically be profitable

One mistake I made early was thinking that publishing more would automatically lead to more royalties.

It does not work that way.

Publishing more bad books just creates more bad data.

The quality of the niche, title, cover, and product page matters a lot.

Another thing I learned is that revenue is not the same as profit.

A book can generate royalties, but if ads are too expensive or the margin is too low, the real profit can be much smaller than it looks.

So I started tracking:

royalties

ad spend

profit per book

click-through rate

conversion rate

organic sales

which niches showed repeat demand

Ads were useful, but not because they magically made books sell.

They showed me what was broken.

If people saw the book but did not click, the cover or title was probably the issue.

If people clicked but did not buy, the product page, price, reviews, or book concept needed work.

That helped me improve faster.

My current view is that Amazon KDP is simple, but not easy.

The simple version is:

You create a book.
You publish it on Amazon.
Amazon handles printing and shipping.
You earn royalties when it sells.

The difficult part is everything before and after publishing:

Choosing the niche.
Creating something useful.
Making a good cover.
Writing a clear title.
Testing ads carefully.
Improving based on data.

AI can speed up parts of the process, but it does not replace judgment.

If anything, AI makes it easier to publish quickly, which also means it is easier to publish low-quality books quickly.

After 109 books, my main takeaway is this:

One book is a gamble.
A catalog gives you more data.

But the catalog only helps if you keep improving the process.

KDP is not passive at the beginning.

At the start, it is research, publishing, testing, fixing, and learning.

The passive part only has a chance to happen later, after you have built something that actually sells.

I’m documenting the process inside a Skool for anyone interested in Amazon KDP + AI.

https://preview.redd.it/yfe5skhzmlzg1.png?width=1516&format=png&auto=webp&s=525d497fcb95fb7096cd949be9945d1289a946c8

https://preview.redd.it/x0h89lhzmlzg1.png?width=1448&format=png&auto=webp&s=43652ab8601b12cd1996df25cb7c98f4b9f0ef77

A few months ago, I started a new Amazon KDP account from zero.

No audience.

No existing catalog.

No previous momentum on that account.

I wanted to test whether it was possible to use AI as part of the workflow and build a small catalog of books over time.

So far, I’ve published 109 books.

The account recently passed around $1,100 in monthly royalties, but I don’t want to make this sound easier than it is.

A lot of the books did not perform well.

Some barely sold.

Some broke even.

A few performed much better than expected.

That was probably the biggest lesson for me:

KDP is not about one perfect book.

It is more about building a system, testing ideas, and learning from the data.

AI helped me move faster, especially with:

niche ideas

outlines

book structure

descriptions

keyword research

editing support

formatting support

But AI did not solve the hardest part.

The hardest part is still figuring out what people actually want to buy.

Before publishing a book, I now try to look at:

whether people are already buying in that niche

how strong the competition is

whether the covers on page one are weak or strong

whether I can create something more useful

whether the price and royalty make sense

whether ads could realistically be profitable

One mistake I made early was thinking that publishing more would automatically lead to more royalties.

It does not work that way.

Publishing more bad books just creates more bad data.

The quality of the niche, title, cover, and product page matters a lot.

Another thing I learned is that revenue is not the same as profit.

A book can generate royalties, but if ads are too expensive or the margin is too low, the real profit can be much smaller than it looks.

So I started tracking:

royalties

ad spend

profit per book

click-through rate

conversion rate

organic sales

which niches showed repeat demand

Ads were useful, but not because they magically made books sell.

They showed me what was broken.

If people saw the book but did not click, the cover or title was probably the issue.

If people clicked but did not buy, the product page, price, reviews, or book concept needed work.

That helped me improve faster.

My current view is that Amazon KDP is simple, but not easy.

The simple version is:

You create a book.

You publish it on Amazon.

Amazon handles printing and shipping.

You earn royalties when it sells.

The difficult part is everything before and after publishing:

Choosing the niche.

Creating something useful.

Making a good cover.

Writing a clear title.

Testing ads carefully.

Improving based on data.

AI can speed up parts of the process, but it does not replace judgment.

If anything, AI makes it easier to publish quickly, which also means it is easier to publish low-quality books quickly.

After 109 books, my main takeaway is this:

One book is a gamble.

A catalog gives you more data.

But the catalog only helps if you keep improving the process.

KDP is not passive at the beginning.

At the start, it is research, publishing, testing, fixing, and learning.

The passive part only has a chance to happen later, after you have built something that actually sells.

https://preview.redd.it/pl8oo38zllzg1.png?width=1448&format=png&auto=webp&s=964279b53768e18bb6aed6fec79f52615bef97c0

A few months ago, I started a new Amazon KDP account from zero.

No audience.

No existing catalog.

No previous momentum on that account.

I wanted to test whether it was possible to use AI as part of the workflow and build a small catalog of books over time.

So far, I’ve published 109 books.

The account recently passed around $1,100 in monthly royalties, but I don’t want to make this sound easier than it is.

A lot of the books did not perform well.

Some barely sold.

Some broke even.

A few performed much better than expected.

That was probably the biggest lesson for me:

KDP is not about one perfect book.

It is more about building a system, testing ideas, and learning from the data.

AI helped me move faster, especially with:

niche ideas

outlines

book structure

descriptions

keyword research

editing support

formatting support

But AI did not solve the hardest part.

The hardest part is still figuring out what people actually want to buy.

Before publishing a book, I now try to look at:

whether people are already buying in that niche

how strong the competition is

whether the covers on page one are weak or strong

whether I can create something more useful

whether the price and royalty make sense

whether ads could realistically be profitable

One mistake I made early was thinking that publishing more would automatically lead to more royalties.

It does not work that way.

Publishing more bad books just creates more bad data.

The quality of the niche, title, cover, and product page matters a lot.

Another thing I learned is that revenue is not the same as profit.

A book can generate royalties, but if ads are too expensive or the margin is too low, the real profit can be much smaller than it looks.

So I started tracking:

royalties

ad spend

profit per book

click-through rate

conversion rate

organic sales

which niches showed repeat demand

Ads were useful, but not because they magically made books sell.

They showed me what was broken.

If people saw the book but did not click, the cover or title was probably the issue.

If people clicked but did not buy, the product page, price, reviews, or book concept needed work.

That helped me improve faster.

My current view is that Amazon KDP is simple, but not easy.

The simple version is:

You create a book.

You publish it on Amazon.

Amazon handles printing and shipping.

You earn royalties when it sells.

The difficult part is everything before and after publishing:

Choosing the niche.

Creating something useful.

Making a good cover.

Writing a clear title.

Testing ads carefully.

Improving based on data.

AI can speed up parts of the process, but it does not replace judgment.

If anything, AI makes it easier to publish quickly, which also means it is easier to publish low-quality books quickly.

After 109 books, my main takeaway is this:

One book is a gamble.

A catalog gives you more data.

But the catalog only helps if you keep improving the process.

KDP is not passive at the beginning.

At the start, it is research, publishing, testing, fixing, and learning.

The passive part only has a chance to happen later, after you have built something that actually sells.

https://preview.redd.it/hd3fmsjyelzg1.png?width=1516&format=png&auto=webp&s=87ab3708b089de1395ef372452bcac9f363806cd

https://preview.redd.it/3xa94hjyelzg1.png?width=1448&format=png&auto=webp&s=86890795f07175b29f93543e6283723a0e011ff7

A few months ago, I started a new Amazon KDP account from zero.

No audience.

No existing catalog.

No previous momentum on that account.

I wanted to test whether it was possible to use AI as part of the workflow and build a small catalog of books over time.

So far, I’ve published 109 books.

The account recently passed around $1,100 in monthly royalties, but I don’t want to make this sound easier than it is.

A lot of the books did not perform well.

Some barely sold.

Some broke even.

A few performed much better than expected.

That was probably the biggest lesson for me:

KDP is not about one perfect book.

It is more about building a system, testing ideas, and learning from the data.

AI helped me move faster, especially with:

niche ideas

outlines

book structure

descriptions

keyword research

editing support

formatting support

But AI did not solve the hardest part.

The hardest part is still figuring out what people actually want to buy.

Before publishing a book, I now try to look at:

whether people are already buying in that niche

how strong the competition is

whether the covers on page one are weak or strong

whether I can create something more useful

whether the price and royalty make sense

whether ads could realistically be profitable

One mistake I made early was thinking that publishing more would automatically lead to more royalties.

It does not work that way.

Publishing more bad books just creates more bad data.

The quality of the niche, title, cover, and product page matters a lot.

Another thing I learned is that revenue is not the same as profit.

A book can generate royalties, but if ads are too expensive or the margin is too low, the real profit can be much smaller than it looks.

So I started tracking:

royalties

ad spend

profit per book

click-through rate

conversion rate

organic sales

which niches showed repeat demand

Ads were useful, but not because they magically made books sell.

They showed me what was broken.

If people saw the book but did not click, the cover or title was probably the issue.

If people clicked but did not buy, the product page, price, reviews, or book concept needed work.

That helped me improve faster.

My current view is that Amazon KDP is simple, but not easy.

The simple version is:

You create a book.

You publish it on Amazon.

Amazon handles printing and shipping.

You earn royalties when it sells.

The difficult part is everything before and after publishing:

Choosing the niche.

Creating something useful.

Making a good cover.

Writing a clear title.

Testing ads carefully.

Improving based on data.

AI can speed up parts of the process, but it does not replace judgment.

If anything, AI makes it easier to publish quickly, which also means it is easier to publish low-quality books quickly.

After 109 books, my main takeaway is this:

One book is a gamble.

A catalog gives you more data.

But the catalog only helps if you keep improving the process.

KDP is not passive at the beginning.

At the start, it is research, publishing, testing, fixing, and learning.

The passive part only has a chance to happen later, after you have built something that actually sells.

https://preview.redd.it/341ajzvdiizg1.png?width=1448&format=png&auto=webp&s=bc16a8c2c4414940e600446cfb31805c83776b1e

A few months ago, I started a new Amazon KDP account from zero.

No audience.
No existing catalog.
No previous momentum on that account.

I wanted to test whether it was possible to use AI as part of the workflow and build a small catalog of books over time.

So far, I’ve published 109 books.

The account recently passed around $1,100 in monthly royalties, but I don’t want to make this sound easier than it is.

A lot of the books did not perform well.

Some barely sold.
Some broke even.
A few performed much better than expected.

That was probably the biggest lesson for me:

KDP is not about one perfect book.

It is more about building a system, testing ideas, and learning from the data.

AI helped me move faster, especially with:

• niche ideas
• outlines
• book structure
• descriptions
• keyword research
• editing support
• formatting support

But AI did not solve the hardest part.

The hardest part is still figuring out what people actually want to buy.

Before publishing a book, I now try to look at:

• whether people are already buying in that niche
• how strong the competition is
• whether the covers on page one are weak or strong
• whether I can create something more useful
• whether the price and royalty make sense
• whether ads could realistically be profitable

One mistake I made early was thinking that publishing more would automatically lead to more royalties.

It does not work that way.

Publishing more bad books just creates more bad data.

The quality of the niche, title, cover, and product page matters a lot.

Another thing I learned is that revenue is not the same as profit.

A book can generate royalties, but if ads are too expensive or the margin is too low, the real profit can be much smaller than it looks.

So I started tracking:

• royalties
• ad spend
• profit per book
• click-through rate
• conversion rate
• organic sales
• which niches showed repeat demand

Ads were useful, but not because they magically made books sell.

They showed me what was broken.

If people saw the book but did not click, the cover or title was probably the issue.

If people clicked but did not buy, the product page, price, reviews, or book concept needed work.

That helped me improve faster.

My current view is that Amazon KDP is simple, but not easy.

The simple version is:

You create a book.
You publish it on Amazon.
Amazon handles printing and shipping.
You earn royalties when it sells.

The difficult part is everything before and after publishing:

Choosing the niche.
Creating something useful.
Making a good cover.
Writing a clear title.
Testing ads carefully.
Improving based on data.

AI can speed up parts of the process, but it does not replace judgment.

If anything, AI makes it easier to publish quickly, which also means it is easier to publish low-quality books quickly.

After 109 books, my main takeaway is this:

One book is a gamble.
A catalog gives you more data.

But the catalog only helps if you keep improving the process.

KDP is not passive at the beginning.

At the start, it is research, publishing, testing, fixing, and learning.

The passive part only has a chance to happen later, after you have built something that actually sells.

I’m documenting the process inside a free Skool community for anyone interested in Amazon KDP + AI.

Link: https://www.skool.com/kdp-ai-club-7394

My experience testing Amazon KDP with AI for a few months

A few months ago, I started a new Amazon KDP account from zero.

No audience.
No existing catalog.
No previous momentum on that account.

I wanted to test whether it was possible to use AI as part of the workflow and build a small catalog of books over time.

So far, I’ve published 109 books.

The account recently passed around $1,100 in monthly royalties, but I don’t want to make this sound easier than it is.

A lot of the books did not perform well.

Some barely sold.
Some broke even.
A few performed much better than expected.

That was probably the biggest lesson for me:

KDP is not about one perfect book.

It is more about building a system, testing ideas, and learning from the data.

AI helped me move faster, especially with:

• niche ideas
• outlines
• book structure
• descriptions
• keyword research
• editing support
• formatting support

But AI did not solve the hardest part.

The hardest part is still figuring out what people actually want to buy.

Before publishing a book, I now try to look at:

• whether people are already buying in that niche
• how strong the competition is
• whether the covers on page one are weak or strong
• whether I can create something more useful
• whether the price and royalty make sense
• whether ads could realistically be profitable

One mistake I made early was thinking that publishing more would automatically lead to more royalties.

It does not work that way.

Publishing more bad books just creates more bad data.

The quality of the niche, title, cover, and product page matters a lot.

Another thing I learned is that revenue is not the same as profit.

A book can generate royalties, but if ads are too expensive or the margin is too low, the real profit can be much smaller than it looks.

So I started tracking:

• royalties
• ad spend
• profit per book
• click-through rate
• conversion rate
• organic sales
• which niches showed repeat demand

Ads were useful, but not because they magically made books sell.

They showed me what was broken.

If people saw the book but did not click, the cover or title was probably the issue.

If people clicked but did not buy, the product page, price, reviews, or book concept needed work.

That helped me improve faster.

My current view is that Amazon KDP is simple, but not easy.

The simple version is:

You create a book.
You publish it on Amazon.
Amazon handles printing and shipping.
You earn royalties when it sells.

The difficult part is everything before and after publishing:

Choosing the niche.
Creating something useful.
Making a good cover.
Writing a clear title.
Testing ads carefully.
Improving based on data.

AI can speed up parts of the process, but it does not replace judgment.

If anything, AI makes it easier to publish quickly, which also means it is easier to publish low-quality books quickly.

After 109 books, my main takeaway is this:

One book is a gamble.
A catalog gives you more data.

But the catalog only helps if you keep improving the process.

KDP is not passive at the beginning.

At the start, it is research, publishing, testing, fixing, and learning.

The passive part only has a chance to happen later, after you have built something that actually sells.

A few months ago, I started a new Amazon KDP account from zero.

No audience.
No existing catalog.
No previous momentum on that account.

I wanted to test whether it was possible to use AI as part of the workflow and build a small catalog of books over time.

So far, I’ve published 109 books.

The account recently passed around $1,100 in monthly royalties, but I don’t want to make this sound easier than it is.

A lot of the books did not perform well.

Some barely sold.
Some broke even.
A few performed much better than expected.

That was probably the biggest lesson for me:

KDP is not about one perfect book.

It is more about building a system, testing ideas, and learning from the data.

AI helped me move faster, especially with:

• niche ideas
• outlines
• book structure
• descriptions
• keyword research
• editing support
• formatting support

But AI did not solve the hardest part.

The hardest part is still figuring out what people actually want to buy.

Before publishing a book, I now try to look at:

• whether people are already buying in that niche
• how strong the competition is
• whether the covers on page one are weak or strong
• whether I can create something more useful
• whether the price and royalty make sense
• whether ads could realistically be profitable

One mistake I made early was thinking that publishing more would automatically lead to more royalties.

It does not work that way.

Publishing more bad books just creates more bad data.

The quality of the niche, title, cover, and product page matters a lot.

Another thing I learned is that revenue is not the same as profit.

A book can generate royalties, but if ads are too expensive or the margin is too low, the real profit can be much smaller than it looks.

So I started tracking:

• royalties
• ad spend
• profit per book
• click-through rate
• conversion rate
• organic sales
• which niches showed repeat demand

Ads were useful, but not because they magically made books sell.

They showed me what was broken.

If people saw the book but did not click, the cover or title was probably the issue.

If people clicked but did not buy, the product page, price, reviews, or book concept needed work.

That helped me improve faster.

My current view is that Amazon KDP is simple, but not easy.

The simple version is:

You create a book.
You publish it on Amazon.
Amazon handles printing and shipping.
You earn royalties when it sells.

The difficult part is everything before and after publishing:

Choosing the niche.
Creating something useful.
Making a good cover.
Writing a clear title.
Testing ads carefully.
Improving based on data.

AI can speed up parts of the process, but it does not replace judgment.

If anything, AI makes it easier to publish quickly, which also means it is easier to publish low-quality books quickly.

After 109 books, my main takeaway is this:

One book is a gamble.
A catalog gives you more data.

But the catalog only helps if you keep improving the process.

KDP is not passive at the beginning.

At the start, it is research, publishing, testing, fixing, and learning.

The passive part only has a chance to happen later, after you have built something that actually sells.