Linktree Admin https://linktr.ee/admin

This the season of thankfulness. To honor it, I have a little tribute to my friend.

https://scottbranchfield.blogspot.com/2026/11/thankfulness-for-friend.html

hii, I’m currently studying marketing at uni and as part of a group project, we’ve created a new brand called Re:issue.

We’ve started putting together a series of blog posts to introduce the brand, its identity and what we’re trying to achieve with it.

Our first post was called “Meet Reissue: Good Things Do Come Back”. I’d really appreciate it if anyone fancied having a look. The course requires us to get a lot of clicks so thought I’d post it here:)

This is a student-created brand and blog, rather than any sort of well established business. My group have also published a few other posts as part of the project, so feel free to have a look through those too if you’re interested.

Blog: https://reissue26.blogspot.com/2026/10/meet-reissue-good-things-do-come-back.html

Thanks for taking the time to read! This is the first time any of us have ever posted a blog so please be kind as we don’t know what we’re doing 😭

https://rorywrites.blog/14-november-2026-today-was-4000x-better/

I slept in until the early afternoon this morning because I was really tired and wanted to have all of my energies for the play (_ _ ) . . z Z. Ruben was curled up outside my door when I went to leave my room. He’s not supposed to go upstairs but I guess he got lonely waiting for me, and I was sad but also touched. We haven’t seen each other much lately with theater so that has probably made him sad (◞‸◟). Don’t worry, though, I gave him lots of cuddles and kisses.

Call time was at 5:00 PM/17:00. I did some sweeping and mopping and I moved lots of stuff out of the way so that my sister could vacuum the carpet alongside the stage. There is a scene where the actors all line up alongside the stage and throw glitter, so we had to clean that mess up .°˖✧. Jay and my sister and I all gathered around Daisy and we went through lots of stuff.

Then it was time for the second performance to start. It went SO MUCH BETTER than last time, like 4000 times better at least. Something funky happened with the mast and it kept swaying and Greta was holding it up for a while, but then the younger techie came and held the line so that it would stay, and the actress could join the dance. We were a little late on getting the bench out on the stage for this one scene. There was supposed to be a full black-out after the scene before it but it was just a blue-out for some reason 【・_・?】.

Other than those few things everything went really well!! (˶◜ᵕ◝˶) As far as I am aware, nothing else went noticeably wrong. We got the bed off in time, which is good because otherwise I think Scott would’ve killed us. The tech crew was all so happy and we did lots of high-fiving and celebrating after the show was over ⸜(｡˃ ᵕ ˂ )⸝.

My parents came to the show tonight, so after the cast was done doing all of their bows and stuff, we went out onto the stage and found them. My sister and I opted out of going to the cast party tonight, which was a Nerf gun battle. We drove home and on the way we stopped at Taco Bell and my sister and I got some food.

When we got home I went up to my room and tried to pick a movie to watch for like two hours. I have arrived at no decision (ᵕ •ᴗ•). Lowkey I just want to watch Interview with the Vampire again even though it hasn’t even been a month… What can I say, I’m obsessed ɿ(◉◞◉)ɼ.

I literally have been thinking about it constantly and Ao3 is down so I can’t write the alternate ending hurt/comfort fic I have in my brain where Louie goes back to Lestat after their daughter’s death and is really depressed and tries to stay out to watch the sunrise… And then Lestat gets him to go inside and comforts him and they share a coffin and Louie finds the strength to go on although he is still sad… And Lestat learns to be more caring and Louie finds purpose again in the love and happiness he feels when he’s with his husband… (╥ ᴗ ╥)♡.

But anyways. I guess that I could still write it, but I wouldn’t be able to post it for- *sob*- eleven more days. This isn’t even procrastination, for once. I genuinely have so many other things to do right now. Lowkey I don’t think I’ve ever been this busy before. Maybe I’ll have time tomorrow (˶◜ᵕ◝˶).

The sun, now parted from the thick clouds, shines brightly onto the ground. Squinting, Mark looks around. The city looks crisp. It takes him a moment to notice the sounds of people talking while navigating the snow ridden sidewalks and cars moving forward at a slow pace. Wondering why, he looks around. His eyes fall onto untouched snow around him. There must be about a metre of snow that has fallen.

“What’s on your mind?” Susan asks.

“Everything sounds quiet. Quieter than usual,” Mark says while still looking at the snow.

“It’s probably because of all the snow. I heard that after a snowstorm, if there is enough snow then it muffles the surrounding sounds,” Susan replies.

Mark turns his head to his right to look at her. She is looking into his eyes. “You’re right,” he says. He then smiles. “I haven’t thought of that.”

She looks forward and up. “You know, I’m feeling hungry.”

“Do you want to go somewhere to eat?” Mark asks, still looking at her.

“That would be nice,” Susan tells him. “I’ve been in the mood to go to that place down the street. The one that has really good salads.”

It's a few blocks away. Without thinking, he turns his head towards it. It takes him a moment to realize the reason why he looked in that direction. He can hear music coming from it. Background music has always been playing for him. When he was young, he thought that everyone heard it. After some time of asking those around him, he found out that he is the only one who can hear it. Nobody seemed to think much of it. Perhaps it was because he was young and they thought that it was a kid who was making it up.

The music changes based on what is currently happening, or what may happen. Now, it’s a happy and calm kind of music. Whenever the music turns ominous, he knows that something bad is going to happen. There are times when he is able to predict what will be the bad outcome based on what is going on around him.

Focusing on the music, he realizes that is a slight shift of tone in the music from a moment ago. The change must be from Susan bringing up the restaurant.

The restaurant always has many different kinds of salads at their food display. Mark thinks back to the meals they got the last time they were there. It was a few weeks ago. Susan got a Greek salad with some mixed beans and pasta on the side. He got a broccoli salad with some potatoes and lots of beets. Thinking about it makes his mouth water. The food was great. It was fresh. The high fibre, though, was what got them. Lucky for them, not only do they live nearby, they were already home when they felt the need to run to the bathroom. Even luckier than that, they have two bathrooms.

He knows that he has time to change the course of what will happen before the music changes to have a more ominous sound to it.

The shift in the music was different. It’s usually subtle but noticeable. This time, however, it was even harder to notice. It must be from the snow around them.

“Remember what happened last time we were there?” Mark asks.

Susan smiled. “Yeah. It was a good meal. At least until we got home.”

“Even with that, thinking about their food makes me want some,” Mark admits.

Susan gets visibly excited. “I’d love to go. What about you?” she inquires.

Mark takes a deep breath. “Yeah,” he tells her.

They both get up off of the bench, and excitedly go to the restaurant.

Neither of them realize how much snow there still is on the sidewalk for they walked with such excitement and haste that they arrived in no time.

After going through the door, they immediately notice that it’s empty. Alex, the person working behind the counter, looks up and recognizes Mark and Susan. They both have eaten at this location enough times to know everyone who works here. They exchange pleasantries, Mark and Susan order and pay for their salads, and they eat.

Upon finishing, Mark looks at Susan. “How much time do you think we have?” Mark asks.

“Not much,” Susan replies knowingly. “We should bolt home.”

“Let’s at least say our goodbyes,” Mark says.

“Agreed,” Susan tells Mark.

Mark and Susan put their plates away, exchange their goodbyes with Alex, and leave the establishment. Once the door closes behind them, they bolt home.

On their way home, Mark notices the background music isn’t ominous. He thinks that it might be because they went to eat knowing the outcome, and that it isn’t something that will be serious. The music is more of a joyful one. Wind instruments are very present, but with what sounds like some sort of rumbling. Knowing that the rumblings from the ensemble will soon become rumblings of their stomachs, he is glad that they are closer to home than they were before. It’s good to live a little, even with what will come.

im a teenager, and i wanna get a new hobby, so i started to write a blog. is this a good start?

https://whatmoreisoutthere.blogspot.com/

https://everydaywithafrin.blogspot.com/2026/11/forgetfulness.html?m=1

I spent five days testing EverPitch, and this EverPitch Review covers what happened when I used it to create, customize, and run an automated webinar for my freelance marketing consultancy.

I purchased the $37 Commercial version and tested its AI script generation, slide creation, voiceover, registration pages, automated webinar room, audience interaction, and follow-up features.

My goal was simple: create a professional 12-minute webinar explaining how I audit a small company's Google Business Profile and use it to attract potential clients without having to present the same information repeatedly.

After five days, I had created my presentation, collected 20 registrations, welcomed 15 attendees across two sessions, and generated two booked calls.

Those are my actual testing results, not a promise that everyone will achieve the same outcome.

But does EverPitch genuinely make webinar creation easier? Is the $37 Commercial version enough? And is the $197 Bundle worth considering?

Here's everything I discovered.

👉See EverPitch Todays Best Offer and Exclusive Premium Bonus✅

What Is EverPitch?

EverPitch is an AI-powered webinar creation and automation platform designed to turn an idea, topic, document, website link, or existing recording into a complete webinar.

Instead of separately writing a presentation, designing slides, recording narration, preparing a registration page, and organizing follow-up emails, EverPitch brings these activities together.

The platform generates a webinar script, creates presentation slides, adds AI voice narration, and allows users to schedule automated sessions.

One feature I found particularly interesting was its AI Q&A host.

During a scheduled presentation, viewers can submit questions, and the host can respond aloud using information from the webinar itself.

This means I don't necessarily have to sit in front of my computer every time someone watches my presentation.

I can create the content, review it, customize it, schedule it, and share the registration link.

For someone who regularly explains the same service to different prospects, that concept is genuinely appealing.

Why I Decided to Try EverPitch

As a freelance marketing consultant, I regularly explain similar things to different people.

For example, when someone asks how I evaluate a Google Business Profile, I usually walk them through:

• What I examine first.

• How I identify incomplete information.

• Why business categories matter.

• How photos and reviews influence customer decisions.

• What improvements I recommend.

• How someone can request further assistance.

I had considered creating a webinar before, but the preparation always seemed like more work than it was worth.

Writing a presentation was one problem. Designing slides was another. Recording myself was something I kept postponing.

I also didn't want to purchase several separate tools just to produce one presentation.

When I came across EverPitch, I liked the idea of having one platform handle most of those tasks.

The $37 one-time Commercial offer was another reason I decided to test it.

I wasn't expecting it to magically bring hundreds of viewers. I simply wanted to know whether it could help me produce a decent presentation and automate the repetitive parts.

My 5-Day EverPitch Experience

Rather than judging EverPitch after generating one presentation, I used it across five consecutive days.

Here's what I actually did.

Day 1: Purchase, Login and First Webinar Script

My first day was mostly about understanding the dashboard and creating my initial presentation.

After purchasing the $37 Commercial version, I received my login information and entered the platform.

I didn't want to begin with a complicated topic, so I used a straightforward prompt:

"Create a 12-minute webinar explaining how I audit a small business's Google Business Profile, covering common problems and improvements, and ending with an invitation to book a free 20-minute consultation."

I wanted something educational rather than a presentation that immediately pushed an offer.

EverPitch generated the initial webinar script.

My first impression was reasonably positive.

The generated content followed a logical structure, starting with an introduction, moving into the educational section, and eventually introducing the consultation offer.

However, I didn't publish it immediately.

I spent time reading through the entire script and making approximately 15 line-level edits.

Some sentences sounded slightly generic, and I wanted the presentation to reflect how I normally explain things to clients.

I also rewrote the opening because the first few moments of a webinar are important for keeping viewers interested.

My Day 1 result:

• Created my first webinar script.

• Reviewed the generated presentation.

• Made approximately 15 edits.

• Spent around two hours.

• Had a usable starting point for the next day.

One thing I learned quickly is that AI-generated content still deserves human review.

EverPitch gave me a foundation, but I was responsible for making the information accurate and relevant.

Day 2: Designing Slides With Slide Studio

Day two was about turning the script into an actual presentation.

I opened Slide Studio and started reviewing the automatically generated slides.

This was one of the more interesting parts of my EverPitch experience.

Instead of manually rebuilding every slide, I could request changes using ordinary language.

For example, I entered instructions such as:

"Make this slide a before-and-after comparison."

"Shorten these bullet points."

"Use my headshot here."

The platform rebuilt the requested slide, and the voiceover remained aligned after my edits.

That saved time compared with manually adjusting each element and then trying to synchronize the narration again.

I also added my logo and brand color.

My final presentation contained 22 slides.

The overall appearance was clean enough for the type of educational presentation I wanted to deliver.

Was everything perfect? No.

I still checked the slide order, wording, and visual consistency.

I would recommend doing the same rather than assuming the first generated version is ready for an audience.

My Day 2 result:

• Created 22 slides.

• Added my logo and brand color.

• Tested conversational slide editing.

• Checked voiceover synchronization.

• Spent approximately 1.5 hours.

The ability to request slide changes through text was probably my favorite feature on this day.

Day 3: Registration Page, Email Integration and Scheduling

Once my presentation was ready, I moved on to the registration process.

EverPitch includes 31 registration page templates, so I selected one that suited my educational webinar.

I wanted the page to communicate three things:

1. What the presentation would teach.

2. Who would benefit from watching.

3. What viewers could do after completing it.

I then configured the session schedule for 7 PM.

Another detail I appreciated was the automatic timezone display.

Someone registering from another country doesn't have to manually calculate the difference between my scheduled time and theirs.

I also connected my Kit account so I could work with my existing email audience.

My initial list contained 412 subscribers.

After completing the setup, I shared the registration link.

By the end of the day, I had 11 registrations.

I also checked the reminder email functionality.

The reminder was sent automatically, which meant I didn't need to manually contact every registered viewer before the session.

My Day 3 result:

• Selected one registration template.

• Connected Kit.

• Configured the 7 PM schedule.

• Shared the registration link.

• Collected 11 registrations.

• Confirmed that the reminder email was working.

The setup took approximately one hour.

Day 4: Testing the Automated Webinar Room

This was the day I was most interested in.

I wanted to see whether EverPitch could actually present the webinar without requiring me to appear on camera or speak throughout the session.

I scheduled my first automated presentation and joined the room as a viewer.

I also tested the experience using my phone, joining approximately three minutes after the presentation had started.

The late-joining experience worked as expected.

I entered the current presentation rather than having to wait for the webinar to restart.

I then tested the audience chat.

One viewer typed a greeting, and the AI host welcomed them without interrupting the presentation.

I also watched how the platform handled questions.

During this session, the AI host delivered three spoken answers.

I specifically checked whether it would invent information that wasn't included in my webinar.

For example, questions about pricing were not covered in my presentation.

The host declined to answer those questions rather than making up a price.

I actually appreciated that behavior.

An automated host should not confidently invent information just to keep a conversation moving.

By the end of the session, seven of my 11 registrants had attended.

My Day 4 result:

• First automated webinar completed.

• Seven attendees from 11 registrations.

• Tested late joining.

• Tested audience greetings.

• Observed spoken Q&A.

• Checked how the host handled questions outside the presentation.

Total testing time was approximately 45 minutes.

Day 5: Second Session, Analytics and Booked Calls

On the fifth day, I wanted to see whether I could repeat the process without rebuilding everything.

I ran another session using my presentation.

This time, I also reviewed the analytics and checked the follow-up process.

I received nine new registrations for the second cycle.

Eight people attended.

Across both sessions, I had 20 registrations and 15 attendees.

I also sent the replay to two people who requested it.

One viewer had used the chat to ask whether they could speak with someone directly.

I responded personally and arranged a call.

Another call came through the follow-up email.

That brought my total to two booked calls.

I also noticed something worth improving.

The AI host had correctly declined two questions about pricing because I hadn't included pricing information in the presentation.

I decided to add two FAQ slides for future sessions.

That should help answer common questions without requiring viewers to contact me separately.

My Day 5 result:

• Ran another automated session.

• Collected nine additional registrations.

• Welcomed eight attendees.

• Reviewed analytics.

• Sent replay information.

• Arranged two calls.

• Identified improvements for my next webinar.

My testing time was approximately one hour.

My Actual EverPitch Results After Five Days

Here is a breakdown of the numbers I recorded during my testing.

These numbers represent my own small-scale experiment.

My 75% attendance rate is based on 15 attendees from 20 registrations.

I don't consider that a guaranteed result or an industry-wide benchmark.

I also wouldn't assume that everyone using EverPitch will generate two calls.

My results depended on my existing email list, the presentation topic, the audience, and the offer I included.

Still, I was happy with what I achieved in five days.

EverPitch Features I Found Most Useful

After using the platform, these are the features that stood out to me.

1. AI Webinar Script Generation

The script generator takes an initial idea or other supplied content and turns it into a structured presentation.

You can begin with a simple prompt, a guided setup, an uploaded document, a website link, or an existing recording.

I used the prompt method because I already knew what I wanted to explain.

The generated script gave me a useful starting structure.

2. Slide Studio

EverPitch offers 73 slide layouts across 11 visual styles.

I liked having different presentation layouts available without manually designing everything.

You can also request adjustments using text instructions.

This was particularly helpful when I wanted a comparison slide or shorter bullet points.

3. AI Voiceover

The platform offers 30 AI voices and supports 87 languages.

This makes it possible to create narrated presentations without recording your own voice.

I found the voiceover synchronization after slide changes particularly useful.

However, I would still listen to the complete presentation before publishing.

4. Automated Webinar Hosting

This is arguably the main reason someone would consider EverPitch.

After creating and reviewing a webinar, you can schedule recurring automated sessions.

You don't have to personally deliver the same presentation every time.

For someone repeatedly explaining a service or product, this can reduce repetitive work.

5. AI Q&A Host

The host can welcome viewers, sort chat messages, and answer questions aloud.

According to the product information, it draws answers from the webinar content.

Up to 20 spoken answers per session are included.

In my testing, I appreciated that it declined questions about information I hadn't included.

6. Registration Pages

EverPitch includes 31 registration templates.

These pages can display session times in each visitor's timezone.

You can share the registration link or use a join button on your existing website.

7. Automated Emails and Replay Pages

The platform includes reminder emails, follow-up emails, replay pages, and analytics.

I particularly liked not having to manually send reminders before every scheduled presentation.

It also provides templates for different follow-up situations.

8. Payment Integrations

EverPitch supports connections with payment services including Stripe, PayPal, Lemon Squeezy, and Razorpay.

This can be useful when your webinar presents an offer that viewers can purchase.

Payments are directed to your own connected account.

9. Existing Recording Conversion

Another interesting capability is turning an existing recording into an automated webinar.

The platform supports recordings up to 2 GB.

This could be useful if you already have an old presentation or Zoom recording that you want to reuse.

10. Multi-Language Presentations

The platform supports translated and re-voiced webinar versions.

With 87 supported languages, this offers an additional way to prepare presentations for audiences who prefer different languages.

EverPitch Pricing: How Much Does It Cost?

One of the things I checked before purchasing was the pricing structure.

There are two main options presented with the offer.

EverPitch Commercial – $37 One-Time

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The Commercial version is the entry-level option.

It includes:

• AI-generated webinar scripts.

• AI-generated slides and voiceovers.

• Automated webinar hosting.

• Scheduled presentations.

• Spoken Q&A, up to 20 answers per session.

• Registration pages.

• Replay pages.

• Reminder and follow-up emails.

• Analytics.

• 3,000 fresh creation credits every month.

• Three included bonuses.

The listed price is $37 as a one-time payment.

There is no required monthly payment for the core offer.

This is the version I purchased and tested.

For someone creating presentations for their own projects, it provides a substantial starting feature set.

EverPitch Bundle – $197 One-Time

The second option is the EverPitch Bundle, priced at $197 as a one-time payment.

It includes everything in Commercial, with additional features:

• 8,000 monthly creation credits.

• 10 finished webinars that you can rebrand.

• 24 ready-made webinar kits.

• Agency rights to create and run webinars for clients.

• Removal of Powered by EverPitch branding from client webinar pages.

The biggest difference is the additional capacity and client-oriented features.

If you're simply creating presentations for your own projects, Commercial may be sufficient.

However, someone planning to create webinars for multiple clients may find the Bundle more appropriate.

I would compare the additional features against your actual workload before upgrading.

👉Get EverPitch Todays Best Offer and Exclusive Premium Bonus✅

What Are the EverPitch Bonuses?

The offer also includes three bonuses.

Bonus 1: The First 7 Days Playbook

This is a practical guide for getting started.

It breaks the initial setup into smaller daily activities, including creating your first prompt, configuring your pages, setting up emails, and reviewing performance.

I like this approach because a new platform can feel overwhelming when you try to explore every feature immediately.

Bonus 2: The Webinar Title & Hook Bank

This bonus includes 100 hooks covering 10 types of businesses.

It provides fill-in-the-blank headline and opening-line ideas.

For someone who struggles to come up with an interesting webinar title, this can be a useful starting point.

Bonus 3: The After-Webinar Email Pack

This bonus includes seven ready-to-edit follow-up emails.

The templates cover situations such as:

• People who watched the presentation.

• People who left early.

• People who registered but didn't attend.

• People who still have questions.

I consider this particularly useful because follow-up communication is an important part of a webinar process.

EverPitch Pros and Cons

After five days, I have a fairly clear picture of where EverPitch performs well and where it needs some attention.

What I Liked

• Simple prompt-based webinar creation.

• AI-generated scripts provide a useful starting point.

• Slide Studio makes presentation editing easier.

• 73 slide layouts and 11 visual styles.

• 30 AI voices and 87 supported languages.

• Automated webinar scheduling.

• Viewers see their own timezone.

• AI host handles greetings and spoken questions.

• Late viewers can join the ongoing presentation.

• Registration and replay pages are included.

• Reminder and follow-up emails.

• 3,000 monthly creation credits with Commercial.

• One-time entry-level pricing.

• Useful bonuses for new users.

What I Didn't Like

• The first presentation still requires considerable review.

• Generated scripts can contain generic wording.

• You need to bring your own audience.

• Q&A responses depend on information included in the webinar.

• Editing and checking slides takes additional time.

• The initial learning process isn't as instant as the promotional wording might suggest.

• The Commercial and Bundle options have different usage rights.

• AI narration should be reviewed before publishing.

I don't consider these problems serious enough to dismiss the platform, but they're worth understanding before purchasing.

Is EverPitch Beginner-Friendly?

I would say yes, provided you're comfortable learning a new online platform.

You don't need to be an experienced presentation designer or professional narrator to get started.

The general workflow is straightforward:

1. Describe the presentation you want to create.

2. Let the platform generate the initial content.

3. Review the script.

4. Customize your slides.

5. Select the voiceover.

6. Configure your registration page.

7. Schedule the webinar.

8. Share the registration link.

9. Review the results.

My recommendation is to begin with a short presentation rather than immediately creating a 60-minute webinar.

A focused 10–15-minute presentation is easier to review, edit, and test.

Once you understand the workflow, you can experiment with longer presentations.

Who Should Consider EverPitch?

Based on the features and my experience, I can see several types of users benefiting from it.

Freelancers and consultants: Explain services, demonstrate expertise, and invite potential clients to book consultations.

Coaches and educators: Create repeatable teaching sessions without personally delivering every presentation.

Affiliate marketers: Explain product features and present recommendations with a clear next step.

Small companies: Demonstrate software, explain services, and educate potential customers.

Content creators: Repurpose existing material into structured webinar presentations.

Agencies: The Bundle may be worth evaluating if you plan to create and manage webinars for clients.

Who Might Not Need EverPitch?

I wouldn't recommend purchasing it simply because AI webinars sound interesting.

You might not need it if:

• You rarely create presentations.

• You prefer delivering every webinar personally.

• You don't have a topic worth presenting.

• You expect the platform to find viewers automatically.

• You don't want to review AI-generated content.

• You only need a basic slide presentation.

EverPitch can help produce and present webinar content, but it cannot replace having something useful to teach or an audience interested in learning.

Is EverPitch Worth It?

After five days, my opinion is positive.

The most valuable part wasn't any single AI feature.

It was having the script, slides, narration, registration page, scheduled presentation, and follow-up process available together.

Before testing EverPitch, I had postponed creating webinars because I didn't want to spend days preparing everything.

During my testing, I managed to create a 12-minute presentation, customize it, schedule sessions, and test the audience experience.

I spent approximately six hours across five days.

I also recorded 20 registrations, 15 attendees, and two booked calls.

For my particular situation, the $37 Commercial purchase was worthwhile.

However, I would separate the value of the platform from the results of my webinar.

EverPitch helped me prepare and deliver the presentation. My existing audience and the usefulness of the topic helped bring people into the room.

Someone starting with no audience should not expect the same registration numbers.

If you already have an email list, social following, website visitors, or potential customers to invite, the platform becomes more interesting.

Frequently Asked Questions About EverPitch

1. What is EverPitch used for?

EverPitch is used to create, customize, and automate webinars. It generates scripts, presentation slides, and AI voiceovers, then provides scheduling, registration, audience interaction, and follow-up features.

2. How much does EverPitch cost?

The Commercial version is listed at $37 as a one-time payment. The optional Bundle is listed at $197 as a one-time payment and includes additional creation credits, ready-made webinars, webinar kits, and agency rights.

3. Does EverPitch require a monthly payment?

The advertised core Commercial offer is a one-time purchase without a required monthly payment. It includes 3,000 fresh creation credits every month.

4. Do I need to appear on camera?

No. You can create narrated presentations using the available AI voices without recording yourself on camera.

5. Can EverPitch create slides automatically?

Yes. It generates slides using 73 layouts across 11 visual styles. You can also request changes through text instructions.

6. How many languages does EverPitch support?

The platform advertises 87 supported languages for AI voiceovers and translated webinar versions.

7. Does EverPitch answer audience questions?

Yes. Its AI host can respond aloud using information from the webinar content. The Commercial offer includes up to 20 spoken answers per session.

8. Can viewers join after the webinar starts?

Yes. The automated room supports late joining, allowing viewers to enter the presentation at its current point.

9. Does EverPitch provide visitors or registrations automatically?

No. You need to promote your registration link through your own email list, website, social media, advertising, or other audience sources.

10. What happens when I run out of creation credits?

The Commercial offer includes 3,000 fresh creation credits each month. Existing webinars continue running even when your creation credits run out.

11. Can I create webinars for clients?

The $197 Bundle explicitly includes agency rights to create and run webinars for clients. Commercial is described as being for your own projects, so anyone planning client work should check the applicable terms before purchasing.

12. Does EverPitch include a money-back guarantee?

The offer advertises a 30-day guarantee. According to the stated terms, you can contact support within 30 days of purchasing to request a refund through JVZoo.

13. Is the EverPitch Bundle worth buying?

It depends on how frequently you plan to create webinars. The additional 8,000 monthly credits, 10 rebrandable webinars, 24 ready-made kits, and agency rights may make it attractive to people managing several client projects.

14. Can I use an existing recording?

Yes. EverPitch supports converting existing recordings into automated webinar experiences. The advertised maximum recording size is 2 GB.

15. Is EverPitch suitable for beginners?

Yes. The prompt-based creation process and included setup playbook make it approachable for beginners. However, you should still review scripts, slides, and voiceovers before publishing.

My Final Verdict: Would I Buy EverPitch Again?

After spending five days using EverPitch, I can say that it solved a problem I had been putting off for quite some time.

I wanted a professional webinar but didn't want to spend several days writing scripts, designing slides, recording narration, and preparing the surrounding presentation process.

EverPitch brought those activities together.

My favorite parts were the script generation, conversational slide editing, automated webinar room, and spoken Q&A host.

I also appreciated the fact that the platform didn't automatically invent answers when viewers asked questions about information I hadn't included.

There are limitations.

You still need to review the generated content, bring your own audience, and create an offer or presentation that genuinely helps viewers.

The platform doesn't guarantee registrations, sales, or booked calls.

But if your goal is to turn your knowledge or existing content into repeatable webinar presentations, I think EverPitch is worth considering.

For my needs, the $37 Commercial version was a reasonable starting point.

I would look at the $197 Bundle only if I needed the additional creation capacity, ready-made materials, and agency rights.

My final recommendation: EverPitch is a useful AI webinar creation and automation platform for freelancers, consultants, educators, creators, and marketers who want to spend less time preparing presentations and more time improving the actual content and reaching their audience.

My five-day experiment was encouraging, and I plan to improve my existing presentation with additional FAQ slides before testing it with another audience.

That's a more realistic way to judge this platform than expecting an AI tool to do absolutely everything.

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Disclosure: This review reflects my stated five-day testing experience. Results are personal and will vary depending on your topic, audience, presentation quality, and promotion efforts. I am not claiming that the results described here are typical or guaranteed.

I have been using different AI platforms for freelance content creation, research, marketing campaigns, and everyday productivity for quite some time. So when I came across GPTHub AI, I was interested in finding out whether it could genuinely make my workflow easier or was simply another tool with an attractive promotional offer.

The biggest selling point was its advertised collection of GPT models, including GPT-6 Astra, GPT-6.1 Sol, Terra, Luna, and additional creative features, all presented through one dashboard.

The introductory price was another reason I decided to try it. Instead of committing to another expensive monthly plan, the advertised offer was just $14.95 as a one-time payment.

I purchased it and spent five days putting it through practical assignments.

I didn't want to judge GPTHub AI based on a few impressive-looking demonstrations. I wanted to see how it handled actual freelance work, including writing articles, preparing emails, analyzing research, creating advertisements, and solving a small coding problem.

My experience was better than I initially expected. I recorded approximately 11.6 hours saved across five days and generated 35 deliverables.

Here is my detailed GPTHub AI review, including what I liked, what disappointed me, the advertised bundle, pricing, potential upgrades, advantages, disadvantages, and my final recommendation.

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GPTHub AI at a Glance

• Product name: GPTHub AI

• Product type: Multi-model AI workspace

• Testing duration: 5 days

• Advertised introductory price: $14.95 one-time

• Main advertised model: GPT-6 Astra

• Additional models: GPT-6.1 Sol, Terra, and Luna

• Image generation: GPT Image 2.5 advertised

• Long-context functionality: Advertised 1-million-token capacity

• Reasoning options: Fast, Deep, and Max

• Prompt templates: Included

• Commercial usage: Advertised commercial license

• Guarantee: 30 days, according to the offer

• Ideal audience: Freelancers, marketers, writers, agencies, and content creators

My verdict in brief: GPTHub AI offers an interesting way to organize different AI workflows in one place. I found the model-selection approach and long-document workflow particularly useful. However, buyers should verify the advertised model specifications and account entitlements instead of assuming that the platform provides identical access to every official OpenAI plan.

What Exactly Is GPTHub AI?

GPTHub AI is an AI workspace designed to bring multiple GPT models and creative functions together through a centralized interface.

The basic concept is straightforward.

You log into the dashboard, select the model you want, enter your instructions, and generate the required output.

Instead of maintaining several separate AI interfaces, the platform aims to make different tasks available from one location.

The advertised model lineup includes GPT-6 Astra, GPT-6.1 Sol, GPT-6.1 Terra, GPT-6 Luna, and earlier GPT versions.

The promotional package also mentions GPT Image 2.5, GPT Live, future model additions, and other advanced capabilities.

What caught my attention was the idea of choosing different models for different assignments.

For example, writing a short product description doesn't require the same approach as analyzing several research reports or troubleshooting a complicated programming issue.

Having multiple options in one workspace sounded practical.

I decided to test that concept instead of simply accepting the promotional claims.

Why I Bought GPTHub AI

My biggest frustration with my existing workflow was the amount of time I spent moving between AI applications.

On some days, I would work on three blog articles, prepare an email sequence, create advertising variations, and analyze research material for a client.

Each task required slightly different instructions and output styles.

I also found myself repeatedly rewriting prompts because the initial responses weren't structured the way I needed.

I was looking for something that could help me:

• Prepare content drafts more quickly.

• Summarize lengthy research material.

• Create multiple advertising variations.

• Develop landing page copy.

• Organize ideas for digital products.

• Help with basic coding problems.

• Reduce unnecessary switching between tools.

GPTHub AI appeared to cover several of these requirements.

The $14.95 introductory offer made it an affordable experiment compared with committing to another expensive monthly AI plan.

I decided to track my results over five days and compare them with my usual working process.

My Five-Day GPTHub AI Testing Experience

I tested GPTHub AI using different assignments rather than repeating the same prompt.

Here is my recorded overview.

Overall results:

• 35 total deliverables.

• Approximately 11.6 hours saved.

• 26 outputs usable without major editing.

• Approximately 74% ready without substantial revisions.

These are my own recorded results, not guaranteed performance figures for everyone.

Day 1: First Login and Initial Impressions

I started testing GPTHub AI on Tuesday evening.

My first task was exploring the dashboard and understanding how the different options were organized.

I logged in through my browser and spent approximately four minutes familiarizing myself with the interface.

I found the central chat workspace, model selector, and prompt templates relatively straightforward.

I didn't want to begin with a complicated assignment, so I selected three simple tasks.

First, I requested a blog introduction.

I gave it a topic and asked for approximately 600 words.

The output had a reasonable structure, with an introduction, supporting paragraphs, and a natural transition into the main subject.

It wasn't perfect, though.

Some phrases sounded generic, so I rewrote those sections before considering it ready.

Next, I tested email writing.

I asked GPTHub AI to prepare a three-email sequence for a promotional campaign.

The first email introduced the offer, the second explained the benefits, and the third encouraged the reader to take action.

Two emails were surprisingly close to my expectations.

The third required a stronger opening and a more conversational ending.

My third experiment was image generation.

I used the advertised GPT Image functionality to create a simple visual for a lead magnet.

The result was acceptable for a basic promotional graphic.

I wouldn't consider it a replacement for professional design work, but it was useful for exploring the creative side of the platform.

I finished the first day with six generated outputs.

Only two were ready without significant changes.

That was a reasonable beginning, but I wanted to test something more demanding.

Day 2: Using GPTHub AI for Long Documents

Wednesday was probably the day I became more interested in the platform.

I had a 62-page client research PDF that needed to be converted into a structured summary.

Normally, this would involve reading the material, identifying important information, organizing the findings, and preparing a concise report.

I selected GPT-6 Astra and supplied the research material.

My instructions were specific.

I wanted:

• The most important findings.

• Major market observations.

• Contradictions within the research.

• Three opportunities.

• Two potential risks.

• A structured conclusion.

The response arrived in approximately 90 seconds.

What I appreciated was the organization.

Rather than simply summarizing everything into a few paragraphs, it separated the information into sections that were easier to review.

It also provided page-level references.

I checked six claims against the original material, and all six were accurate.

That was encouraging, although I wouldn't treat a small sample of verified claims as proof of perfect accuracy.

I also compared Astra and Terra for a strategy-related question.

Astra provided a more detailed explanation, while Terra returned a quicker, shorter response.

This was a useful demonstration of why having different model options could be beneficial.

My recorded time comparison was:

The biggest difference was that I could move from one assignment to another without repeatedly changing applications.

Day 2 verdict: The document-analysis workflow was one of my favorite parts of testing GPTHub AI.

Day 3: My Biggest Research Assignment

On Thursday, I decided to give the platform a more challenging assignment.

A client needed a competitor analysis covering several areas:

• Market positioning.

• Competitor features.

• Pricing differences.

• Potential market gaps.

• Recommendations.

I supplied approximately 180 pages across three research documents.

I asked Astra to prepare a detailed report exceeding 40 pages.

The first draft was generated in approximately six minutes.

The result was a 47-page report.

I was impressed with the initial structure, but I didn't send it directly to the client.

I spent approximately 50 minutes reviewing the information, checking important figures, and improving the recommendations.

During that process, I discovered one pricing error. The response had mixed up two competitor tiers.

This is something worth remembering when using AI for research.

An impressive-looking report isn't necessarily a completely accurate report.

I corrected the information, refined a few sections, and sent the final version to the client on Thursday evening.

The client approved it with two minor changes.

Day 3 verdict: GPTHub AI saved me considerable time preparing the initial research report, but verification was still essential.

Day 4: Creating Multiple Marketing Deliverables

Friday was my content production day.

I wanted to see how GPTHub AI would perform when I gave it several different marketing assignments.

I worked on landing pages, advertisements, and product descriptions.

My results were:

Landing pages: I prepared two landing page drafts, including headlines and supporting sections. Both were usable after my review.

Social media advertisements: I requested six variations for Facebook and Instagram. Five were close to my requirements, while one needed a different approach.

Product descriptions: I generated three descriptions for different products. All three required only minor polishing.

I also experimented with model selection.

I used Luna for faster advertising variations, Astra for more detailed landing page copy, and Sol for straightforward product descriptions.

This was one of the more practical features during my testing.

I didn't need to use the same model for every task.

The complete batch took approximately two hours.

My usual process would take around 4.5 to 5 hours.

That meant I finished considerably earlier than expected.

Day 4 verdict: For repetitive content production, the ability to switch between different models made the workflow more convenient.

Day 5: Coding Assistance and Course Development

On Saturday, I wanted to explore something beyond writing and marketing.

I selected two assignments.

Experiment 1: Fixing a JavaScript issue

A client's landing page had a JavaScript problem that was preventing a form from working properly.

I'm not a developer, so I initially thought about hiring someone to investigate it.

Instead, I pasted the relevant code snippet into Astra's coding mode and explained the problem.

It identified a scope-related issue and suggested a correction.

I applied the suggested change and tested the form.

It worked.

The complete process took approximately 15 minutes.

For a relatively straightforward problem, that was a useful experience.

However, I wouldn't use an AI-generated code correction without testing it, especially on a live website.

Experiment 2: Creating an email marketing course outline

My second assignment was developing a 12-module course outline.

I requested module descriptions, learning objectives, and suggested exercises.

The initial response gave me a useful structure.

Approximately 85% of the material was suitable for my requirements.

I reorganized one module and added two missing topics.

The biggest advantage was that I could begin with a structured outline instead of staring at a blank page.

Day 5 verdict: GPTHub AI was useful beyond article writing. I could also use it for planning, basic troubleshooting, and organizing educational content.

GPTHub AI Features Explained

After five days, these are the main features I would pay attention to.

1. GPT-6 Astra

Astra is presented as the flagship model in the promotional package.

The offer emphasizes complex reasoning, long-context processing, and handling demanding assignments.

My research tests were the most relevant examples of where I found this approach useful.

For detailed reports, structured analysis, and complicated writing tasks, I preferred the more comprehensive responses.

The actual model identity and capabilities should be confirmed within the account.

2. Multiple GPT Models

The advertised model lineup includes Sol, Terra, Luna, Astra, and previous versions.

This is useful because different assignments have different requirements.

A quick email response doesn't need the same depth as a long research report.

I appreciated having the option to choose rather than treating every task identically.

3. One-Million-Token Long-Context Mode

The promotional offer highlights a one-million-token context capability.

The purpose is to allow users to work with substantial amounts of material in one session.

Potential applications include:

• Long research reports.

• Entire books.

• Extensive business documents.

• Large codebases.

• Multiple source files.

• Long-form content planning.

My 62-page document test was positive.

Still, actual upload limits, processing limits, and model availability should be checked in the activated account.

4. Fast, Deep, and Max Reasoning

The offer describes three main thinking options.

Fast is intended for everyday assignments.

Deep is intended for more detailed analysis.

Max is promoted for demanding problems.

I like this concept because it encourages users to match the processing approach to the task.

5. Side-by-Side Model Comparison

The advertised multi-model workspace allows users to switch between models and compare responses.

This could be useful for copywriting, research, brainstorming, and content development.

For example, you might ask two models to prepare different landing page headlines and then compare which one better suits your audience.

6. Built-In Prompt Engine

The platform includes ready-made prompt templates for various assignments.

These cover areas such as:

• Sales copy.

• Email sequences.

• Advertising.

• Scripts.

• Funnels.

• Content creation.

For beginners, this is a helpful starting point.

You don't need to understand advanced prompt engineering before experimenting with common tasks.

7. GPT Image 2.5

Image generation is another advertised component.

It can be useful for creating basic promotional concepts, lead magnet graphics, and social media visuals.

I found my initial result acceptable, but professional designers may still prefer specialized creative applications.

8. Coding and Technical Assistance

The coding feature is promoted for creating and troubleshooting code.

My JavaScript test was positive.

It could be useful for beginners who need explanations, basic scripts, or assistance understanding errors.

Complex software development still requires appropriate testing and technical review.

9. Beginner-Friendly Dashboard

The dashboard was relatively easy to understand.

I didn't need to install a separate desktop application during my initial tests.

The model selector and central chat area made the basic workflow straightforward.

10. Commercial License

The offer advertises commercial usage for freelance projects, agency work, and client assignments.

This could be valuable for people producing content for paying customers.

However, always read the actual license conditions and applicable usage restrictions.

GPTHub AI Bundle: Everything Advertised

One of the things I wanted to examine was the complete package rather than just the main dashboard.

Here are the components mentioned in the promotional offer.

Main GPTHub AI Workspace: The central platform for accessing the advertised models and creative functions.

GPT-6 Astra: The flagship model promoted for reasoning and lengthy assignments.

GPT-6.1 Sol, Terra, and Luna: Additional advertised model options for different workflows.

Previous GPT Models: Earlier versions are also mentioned in the package.

Long-Context Mode: Advertised for working with large documents and extensive research material.

Astra Deep-Think Modes: Fast, Deep, and Max options.

Multi-Model Chat Workspace: Switch between models and compare their responses.

Advanced AI Content Engine: Designed for generating articles, emails, advertising copy, and scripts.

Built-In Prompt Library: Ready-made templates for marketing, content, and other assignments.

High-Converting Copy Generator: Promoted for creating persuasive promotional content.

GPT Image 2.5 Bonus Mode: Additional image-generation functionality.

Commercial License: Advertised for client projects, agencies, and freelance work.

Future Model Updates: The vendor claims that upcoming GPT releases will be added automatically.

Premium GPT-6 Astra Prompt Pack: An additional collection of prompts covering sales pages, email swipes, advertisements, funnels, and research reports.

Astra Code Studio and Astra Agent Mode: Mentioned as additional free extras for the first 100 buyers. Confirm eligibility and availability with the vendor.

The overall package is designed to cover several everyday AI activities from one workspace.

GPTHub AI Pricing: Is $14.95 Worth It?

The advertised introductory price is $14.95 as a one-time payment.

This is considerably lower than the recurring prices commonly associated with premium AI plans.

However, I wouldn't automatically compare the package with an official OpenAI Pro or Enterprise entitlement.

GPTHub AI is presented as an independent platform, and its actual model access, usage limits, and service conditions should be checked separately.

The promotional offer also mentions a 30-day guarantee.

It refers to optional upgrades, but I don't have a complete, verified OTO pricing breakdown.

Therefore, I wouldn't recommend assuming that every additional feature or upgrade is included in the introductory purchase.

My suggestion is simple: evaluate the main package first and only consider additional purchases if they offer something you genuinely need.

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GPTHub AI Pros and Cons

What I Liked

• Multiple advertised models in one interface.

• Easy-to-understand dashboard.

• Useful for blog and email drafts.

• Interesting long-document workflow.

• Different reasoning options.

• Helpful prompt templates.

• Can prepare marketing content quickly.

• Useful for organizing research.

• Coding assistance for basic problems.

• Additional image-generation functionality.

• Commercial usage advertised.

• Affordable introductory price.

• A 30-day guarantee is advertised.

What Could Be Better

• Some generated content needs substantial editing.

• Research information must be checked.

• The initial image-generation result wasn't premium quality.

• Actual model availability should be verified.

• Future model additions haven't been independently established through my five-day test.

• Complete optional upgrade pricing wasn't available in the offer information I reviewed.

• Five days is insufficient to judge long-term reliability.

• It shouldn't be assumed to provide identical entitlements to official OpenAI plans.

I believe these are important considerations for anyone evaluating GPTHub AI.

GPTHub AI vs Using Separate AI Applications

I wouldn't say that GPTHub AI automatically replaces every specialist application.

However, its centralized approach has some practical advantages.

When using several separate tools, you may need to manage different interfaces, organize prompts repeatedly, and move information between applications.

GPTHub AI aims to bring different model options into one workspace.

During my testing, this made switching between writing, research, and content-generation assignments easier.

Dedicated tools may still be better for specialized editing, advanced integrations, or particular creative workflows.

I see GPTHub AI as a potentially convenient central workspace rather than a guaranteed replacement for every application.

Who Should Buy GPTHub AI?

Based on my experience, I think the following users may find it useful.

Freelance writers: For article outlines, blog drafts, emails, and editing assistance.

Affiliate marketers: For promotional content, product descriptions, campaign ideas, and email sequences.

Digital marketers: For advertising concepts, landing page copy, and content planning.

Content creators: For video scripts, social media ideas, and promotional graphics.

Researchers: For organizing lengthy documents and preparing initial research summaries.

Small agencies: For managing repetitive writing and marketing assignments.

Beginners: For experimenting with AI models through a relatively straightforward interface.

Who Should Avoid It?

I would be cautious if you expect:

• Perfect outputs without editing.

• Guaranteed income from purchasing an AI tool.

• Independently verified access to every advertised model.

• Unlimited processing without usage restrictions.

• Professional design quality from every generated image.

• Guaranteed long-term availability of all future models without checking the terms.

The best purchase is one that solves an actual problem in your workflow.

Is GPTHub AI Legit?

This is a reasonable question, especially when the advertised introductory price is only $14.95.

My five-day testing experience was positive.

I used the platform for content creation, document analysis, marketing assignments, and basic coding assistance.

It helped me prepare several useful drafts and reduce the time spent on repetitive tasks.

However, there is a difference between testing a platform's practical functionality and independently verifying every promotional technical claim.

I haven't independently established every claim regarding GPT-6 Astra, one-million-token processing, premium-plan equivalence, or future model additions.

The promotional information also identifies GPTHub AI as an independent platform rather than an official OpenAI product.

My recommendation is to review the actual checkout details, account terms, privacy arrangements, and support information before purchasing.

Frequently Asked Questions About GPTHub AI

1. What is GPTHub AI used for?

It is advertised as a multi-model AI workspace for writing, research, content creation, marketing, image generation, and coding assistance.

2. How much does GPTHub AI cost?

The introductory offer I reviewed displayed a one-time price of $14.95. Check the current checkout page for the latest price.

3. Does GPTHub AI require a monthly payment?

The introductory package is advertised as a one-time purchase without recurring monthly fees. Check the terms for optional upgrades and any additional charges.

4. Does GPTHub AI include GPT-6 Astra?

GPT-6 Astra is advertised as part of the package. Confirm its actual availability and functionality after account activation.

5. Is GPTHub AI suitable for beginners?

Yes, it is marketed toward beginners. I found the dashboard relatively easy to understand during my first session.

6. Can I use GPTHub AI for client projects?

The offer advertises a commercial license for freelance and agency work. Read the actual license terms before using generated outputs commercially.

7. Can GPTHub AI generate images?

The promotional package includes GPT Image 2.5 functionality.

8. Does GPTHub AI support large documents?

The vendor advertises a one-million-token long-context mode. My own testing included a 62-page PDF and a larger multi-document research assignment.

9. Do I need programming knowledge?

No programming knowledge was necessary for my basic tests. The platform also advertises coding assistance for users who need help with technical tasks.

10. Does GPTHub AI have a refund guarantee?

The offer states that purchases are protected by a 30-day money-back guarantee. Check the applicable terms and contact instructions.

11. Are there additional upgrades?

The offer mentions optional upgrades, but a complete itemized OTO pricing list wasn't available in the information I reviewed.

12. Does it include future GPT updates?

The vendor advertises automatic future model additions. This is a long-term promise that I haven't independently verified.

Final Verdict: Should You Buy GPTHub AI?

After five days of testing, I have a much clearer idea of where GPTHub AI fits into my daily workflow.

I particularly liked the flexibility of choosing different models for different assignments.

The long-document workflow was another highlight. Being able to prepare a structured research summary without manually organizing every section saved me considerable time.

I also found the prompt library useful for repetitive writing assignments.

The coding assistance was an unexpected bonus, and the image-generation functionality provided another creative option.

However, I wouldn't describe GPTHub AI as a perfect replacement for every AI platform.

Generated information still needs verification. Some content requires editing, and the actual technical specifications and long-term promises should be checked rather than accepted automatically.

The most important result from my testing was the time saved.

I generated 35 deliverables over five days and recorded approximately 11.6 hours saved compared with my usual workflow.

That is a meaningful improvement for someone who regularly works with content, marketing, and research assignments.

Would I purchase it again at the advertised $14.95 introductory price? Yes.

Would I recommend it to every person simply because it includes several advertised GPT models? No.

I would recommend evaluating it if you regularly use AI for multiple types of work and want to explore a centralized interface.

My final rating is 8.5/10 based on my five-day practical experience.

GPTHub AI has an interesting combination of features, a relatively accessible introductory price, and a workflow that I found useful.

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Just remember to verify important outputs, understand the actual usage terms, and make your purchase decision based on the features you genuinely need rather than the biggest promotional promises.

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GPTHub AI Review – Is this all-in-one AI workspace really worth $14.95? I spent five days testing GPTHub AI for content creation, long-document research, email writing, landing pages, coding assistance, and other everyday freelance tasks. I wanted to find out whether it could genuinely simplify my workflow or was simply another AI tool making bigger promises than it could deliver.

My initial reaction was skepticism. The advertised combination of GPT-6 Astra, multiple GPT models, image generation, and a one-time $14.95 payment sounded almost too good to be true.

However, I decided to put it through practical assignments instead of judging it by promotional claims. I recorded the time spent, outputs generated, editing required, and the number of deliverables I could actually use.

After five days, I had produced 35 deliverables and estimated that I saved approximately 11.6 hours compared with my usual workflow.

Here is my complete GPTHub AI review, including my testing experience, features, advantages, disadvantages, pricing, bonuses, bundle details, and whether I think it is worth considering.

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GPTHub AI Review: Quick Overview

• Product: GPTHub AI

• Category: Multi-model AI workspace

• My testing period: 5 days

• Advertised introductory price: $14.95 one-time

• Main advertised model: GPT-6 Astra

• Other advertised models: Sol, Terra, Luna, and previous GPT versions

• Additional feature: GPT Image 2 generation

• Long-context capability: Advertised 1-million-token mode

• Thinking modes: Fast, Deep, and Max

• Prompt library: Included

• Commercial usage: Commercial license advertised

• Device compatibility: Browser-based, according to the offer

• Guarantee: 30 days, according to the offer

• Best suited for: Freelancers, writers, marketers, content creators, and people regularly working with AI.

My initial verdict: GPTHub AI deserves consideration if you want a centralized workspace for different AI tasks. Its most interesting advertised feature is the ability to switch between models instead of relying on one model for everything. My five-day experience was positive, although I would not treat every promotional performance claim as independently verified.

What Is GPTHub AI?

GPTHub AI is presented as an all-in-one AI workspace that brings several GPT models together through a single dashboard.

Instead of maintaining separate interfaces for different AI tasks, the idea is to choose a suitable model, enter a prompt, and generate the required output.

During my testing, I primarily used it for freelance content assignments. These included blog introductions, email sequences, research summaries, competitor analysis, landing page copy, social media advertisements, product descriptions, and basic coding assistance.

The advertised model lineup includes:

• GPT-6 Astra for complex reasoning and longer assignments.

• GPT-6.1 Sol for everyday tasks.

• GPT-6.1 Terra for faster, practical responses.

• GPT-6 Luna for high-volume generation.

• Earlier GPT versions.

• GPT Image 2.5 for image creation.

• GPT Live for real-time voice interactions, as described in the updated offer.

The actual model availability and capabilities should be checked inside the activated account. The product's promotional claims about OpenAI models, premium-tier equivalence, and future model additions should not automatically be interpreted as direct OpenAI plan entitlements.

What interested me most was the multi-model approach.

I frequently switch between different AI tools depending on the assignment. Having those options presented in one workspace could make the process considerably easier.

Why I Decided to Test GPTHub AI

My main problem wasn't a shortage of AI tools. It was having too many of them.

I regularly work on articles, promotional emails, research assignments, landing pages, and client projects. Each assignment requires a slightly different approach.

Sometimes I need a quick response. Other times, I need a detailed analysis of several documents. For certain assignments, I need creative writing, while technical problems require a more structured approach.

I was spending too much time switching between tools and adjusting prompts.

When I came across GPTHub AI, three things caught my attention:

1. The advertised $14.95 one-time introductory price.

2. The possibility of switching between multiple GPT models.

3. The advertised long-context functionality for handling larger documents.

I purchased it on Tuesday evening and began testing it immediately.

I wasn't expecting every generated response to be perfect. My actual objective was to determine whether it could reduce repetitive work without creating additional editing headaches.

My 5-Day GPTHub AI Experience

Here is the testing log I maintained during the five-day period.

Five-day result:

• Approximately 11.6 hours saved.

• 35 deliverables generated.

• 26 deliverables considered ready without major editing.

• Approximately 74% of outputs were usable without substantial revisions.

These are my recorded results, not guaranteed outcomes for other users.

Day 1: Getting Started and Exploring the Dashboard

I started around 8 PM on Tuesday.

My first objective was simply understanding how the platform worked.

I logged in through my browser and explored the dashboard. I didn't have to install a separate desktop application during my initial setup.

It took approximately four minutes to understand the basic layout.

The model selector was on the left, the main chat workspace occupied the center, and the prompt templates were available on the right.

I wanted to test three different types of output before attempting anything complicated.

Test 1: Blog introduction

I entered a prompt asking for a 600-word introduction on a relatively ordinary finance topic.

The response was reasonably structured. The opening was interesting, and the paragraphs followed a logical sequence.

However, some sentences felt generic. I had to rewrite a few sections before I was comfortable using the output.

Test 2: Email sequence

Next, I requested a three-email sequence.

This was more interesting.

The first email introduced the subject, the second explained the benefits, and the third encouraged the reader to take action.

Two of the three emails were close to what I wanted. The remaining one needed a stronger opening and a more natural closing.

Test 3: Image generation

I also tried GPT Image 2 for a simple lead magnet visual.

The result was acceptable for a basic promotional graphic. However, I wouldn't use that initial output as a premium agency hero image without further refinement.

I finished the first day with six test outputs.

Two were ready to use, while the others required varying degrees of editing.

My Day 1 takeaway: The interface was easier to understand than I expected. The prompt library was particularly useful because it gave me a starting point instead of forcing me to write every instruction from scratch.

Day 2: Testing the Long-Context Feature

Wednesday was when GPTHub AI became more interesting.

I had a 62-page market research PDF that needed to be summarized for a client.

Normally, I would spend several hours reading the material, identifying important findings, organizing information, and preparing a structured summary.

This time, I selected GPT-6 Astra and supplied the material with specific instructions.

I requested:

• Key findings.

• Important market observations.

• Contradictions within the research.

• Three potential opportunities.

• Two significant risks.

• A structured conclusion.

The response arrived in approximately 90 seconds.

What impressed me was how it organized the information. Instead of producing a generic summary, it separated the findings into useful sections.

It also included page-level references in its response.

I checked six claims against the original material, and all six matched what I found.

That gave me considerably more confidence in using the platform for document-heavy assignments, although six correct checks are not proof that every statement will always be accurate.

Here is how my time compared:

I also experimented with Deep-Think mode and compared Astra with Terra.

Astra produced a more layered response to my strategy question. Terra was quicker, although its response was less detailed.

This helped me understand why switching models can be useful.

Not every assignment requires the most elaborate response.

My Day 2 takeaway: Long-document analysis was one of the strongest parts of my testing experience. I still recommend checking important figures and statements, but having a structured first draft available quickly made a noticeable difference.

Day 3: Creating a Detailed Research Report

Thursday was my most demanding test.

A client needed a competitor analysis covering market positioning, feature differences, pricing comparisons, and recommendations.

I supplied approximately 180 pages across three research documents.

My instruction was to prepare a structured report of more than 40 pages.

I used Astra for the task because I wanted a detailed response rather than a short summary.

The first draft took approximately six minutes to generate.

It was a 47-page report.

Naturally, I didn't send it to the client immediately.

I spent approximately 50 additional minutes reviewing the information, checking important figures, correcting a few sections, and improving the recommendations.

During verification, I caught one pricing error where the output mixed up two competitor tiers.

This was an important reminder.

Even when a response looks professional, an AI-generated report can contain incorrect details.

The structure, however, was useful. It covered the requested sections and gave me a strong starting point for the final assignment.

I sent the revised report on Thursday evening, and the client approved it with two minor changes.

My Day 3 takeaway: For research-heavy work, GPTHub AI helped reduce the time required to prepare the first draft. Its output still required human review, particularly when pricing and competitor information were involved.

Day 4: Batch Content Creation

Friday is normally my content production day.

I decided to test how GPTHub AI performed when generating several different deliverables in one session.

I worked on landing pages, social media advertisements, and product descriptions.

My results were:

The model-switching workflow was especially helpful.

I used Luna for advertisement variations because I wanted relatively quick responses.

For landing page copy, I preferred Astra because I needed more detailed structures and persuasive sections.

For product descriptions, I used Sol.

I didn't need the deepest reasoning mode for straightforward product descriptions.

The entire batch took approximately two hours.

My usual process would take around 4.5 to 5 hours.

I was able to finish considerably earlier than expected.

My Day 4 takeaway: The ability to select different models for different tasks was more useful than I initially thought. It helped me avoid treating every assignment as though it required the same type of AI response.

Day 5: Coding Assistance and Course Planning

Saturday was slightly different.

I wanted to test two tasks outside my usual content workflow.

First test: JavaScript troubleshooting

A client's landing page had a JavaScript issue that was preventing a form from working correctly.

I'm not a developer, so I initially considered finding someone to fix it.

Instead, I pasted the relevant code snippet into Astra's coding mode and described the problem.

The response identified a scope-related issue and suggested a correction.

I applied the suggested change and tested the form.

It worked.

The entire process took approximately 15 minutes.

I wouldn't claim that this makes professional developers unnecessary. However, for a relatively straightforward problem, having an explanation and suggested correction in one place was genuinely helpful.

Second test: Creating a mini-course outline

My next task was preparing a 12-module outline for an email marketing course.

I requested module descriptions, learning objectives, and suggested exercises.

The initial response gave me a usable structure.

Approximately 85% of it worked for my intended purpose.

I reorganized module seven and added two topics that I felt were missing.

The biggest benefit was that I didn't have to start with a blank page.

My Day 5 takeaway: GPTHub AI wasn't just useful for writing articles. It also helped with basic technical troubleshooting, planning, and organizing information.

My Overall Results After Five Days

After completing the testing period, I reviewed my spreadsheet.

These were the results I recorded:

The results made me more positive about the platform.

However, I want to make one distinction.

Generating 35 deliverables doesn't mean every deliverable was perfect. Some needed rewriting, fact-checking, formatting, or additional instructions.

The real advantage was having a useful first draft much sooner.

For my freelance workflow, that matters.

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GPTHub AI Features: What Makes It Interesting?

Let's look at the major features advertised with the platform and how they relate to my experience.

1. Multiple GPT Models in One Workspace

This is arguably the central attraction.

Rather than relying on one model, GPTHub AI promotes a selection of GPT models for different tasks.

I particularly liked being able to choose a model based on the assignment.

For example:

• Detailed research: Astra.

• Everyday writing: Sol.

• Faster content variations: Luna.

• Practical responses: Terra.

The advertised lineup also includes earlier models and future additions.

The actual availability of particular models should be confirmed after activation.

2. GPT-6 Astra Long-Context Mode

The offer promotes a context capacity of up to one million tokens.

The idea is to work with large documents, lengthy reports, research material, and other substantial inputs without repeatedly splitting everything into smaller sections.

This was the feature I was most interested in.

My 62-page research summary was a positive experience, and the larger competitor analysis was another useful test.

For anyone regularly handling lengthy source material, this capability is worth investigating.

3. Deep-Think Reasoning Modes

The advertised thinking options include:

• Fast.

• Deep.

• Max.

The purpose is to adjust how much reasoning a task requires.

For a short product description, I don't need an elaborate reasoning process.

For competitor research or a complicated strategy assignment, a deeper response is more appropriate.

I like the flexibility of having these options rather than using one setting for everything.

4. Multi-Model Comparison

Another interesting feature is the advertised ability to compare different model outputs side by side.

This can be useful when you're unsure which response is best.

For example, you could request two versions of a landing page introduction and compare the structure, clarity, tone, and persuasiveness.

It is still important to judge the output yourself.

The longest answer isn't necessarily the best answer.

5. Built-In AI Prompt Library

The prompt library was one of the more beginner-friendly elements I explored.

It includes templates for tasks such as:

• Sales copy.

• Emails.

• Advertising.

• Scripts.

• Funnels.

• Content creation.

I used a sales email template during my initial testing.

It provided a helpful starting structure and reduced the amount of prompt preparation I needed.

You can still customize the instructions to match your audience and requirements.

6. GPT Image Generation

The offer also promotes GPT Image 2.5.

This adds another creative option to the workspace.

Potential applications include:

• Lead magnet graphics.

• Blog illustrations.

• Promotional visuals.

• Social media graphics.

• Creative concepts.

My initial image test was acceptable for a simple lead magnet.

However, people producing premium advertising visuals should assess image quality carefully before replacing their existing creative workflow.

7. Coding Assistance

I tested coding assistance using a JavaScript problem.

The suggested correction worked in my particular test.

This makes the feature potentially useful for people who need help understanding small code issues, generating scripts, or troubleshooting basic problems.

For complicated applications, security-sensitive code, or production systems, proper developer review remains important.

8. Commercial Usage

The offer states that a commercial license is included.

It advertises use for freelance assignments, client projects, and agency services.

That could be useful for creators who produce deliverables for paying clients.

Before accepting commercial work, I would still review the actual license terms and any restrictions on generated content.

GPTHub AI Bundle: What Do You Get?

One thing I wanted to understand was whether the introductory purchase included more than the main dashboard.

According to the advertised package, the following items are included.

1. GPTHub AI Main Dashboard

The central workspace for generating content and working with the advertised GPT models.

2. GPT-6 Astra

The flagship model promoted with long-context analysis and advanced reasoning capabilities.

3. Multiple GPT Models

The advertised package includes Sol, Terra, Luna, and previous GPT versions.

4. Long-Context Mode

Designed for handling large documents, books, reports, and lengthy research material.

5. Deep-Think Modes

Fast, Deep, and Max options for different levels of task complexity.

6. Multi-Model Workspace

A centralized interface for switching between models and comparing outputs.

7. Built-In Prompt Library

Ready-made prompts for writing, marketing, emails, scripts, and other common tasks.

8. Commercial License

The offer promotes commercial usage for freelance and client-related projects, subject to the actual license terms.

9. GPT Image 2.5 Bonus Mode

An additional image-generation feature advertised with the package.

10. Premium GPT-6 Astra Prompt Pack

The advertised bonus includes ready-made prompts covering:

• Sales pages.

• Email swipes.

• Advertisements.

• Funnels.

• Long-form reports.

11. Future Model Updates

The vendor states that upcoming GPT releases will be added automatically.

This is an important claim to verify in the account terms, rather than assuming that every future model or capability will necessarily be included indefinitely.

12. Astra Code Studio and Astra Agent Mode

The offer also mentions these as free extras for the first 100 buyers.

I would confirm eligibility and activation with the vendor before counting these as part of the standard package.

Overall, the advertised bundle covers writing, research, image generation, coding assistance, and reusable prompts.

GPTHub AI Pricing: How Much Does It Cost?

The introductory price advertised during the offer is:

<escape>**$14.95 one-time payment.**</escape>

The promotional page also displays a claimed regular value of $597 per month.

I would treat that larger figure as the vendor's promotional comparison rather than an independently established market price.

The advertised introductory package includes the main dashboard, multiple GPT models, long-context functionality, prompt templates, image generation, and the additional prompt pack.

There is also a 30-day money-back guarantee mentioned in the offer.

One important point: the promotional page mentions optional upgrades but does not provide a complete, itemized OTO price list.

Therefore, I wouldn't invent upgrade names or prices.

If additional offers appear after checkout, review each one separately. You should be able to determine whether an upgrade is necessary for your intended workflow before purchasing it.

My recommendation is to evaluate the main package first.

For my five-day test, the basic functionality was enough to complete the assignments I described.

GPTHub AI Pros and Cons

After testing the platform, here is my balanced assessment.

Pros

• Multiple advertised GPT models in one workspace.

• Beginner-friendly dashboard.

• No separate desktop installation required during my initial testing.

• Useful prompt templates.

• Interesting long-document workflow.

• Different reasoning modes for different assignments.

• Helpful for article and email drafting.

• Suitable for preparing initial research reports.

• Can assist with basic coding problems.

• Includes an advertised image-generation feature.

• Commercial usage is promoted.

• Introductory $14.95 one-time offer.

• 30-day guarantee stated by the vendor.

• Future model additions are advertised.

Cons

• AI-generated information still requires verification.

• Some outputs need editing before publication.

• Image generation may not satisfy premium creative requirements.

• The actual availability of advertised models needs confirmation.

• The future-update promise should be checked in the terms.

• The complete OTO pricing structure isn't specified in the promotional information.

• Five days isn't enough to assess long-term stability.

• The introductory offer should not be confused with independently verified premium OpenAI plan entitlements.

I would rather mention these limitations than pretend that every part of the platform is perfect.

GPTHub AI vs Traditional AI Workflows

One reason I found the platform interesting was the possibility of bringing several everyday tasks into one interface.

Here is how I would compare the approaches.

Using separate AI tools:

You may need to switch between different platforms, manage separate interfaces, and repeatedly organize your prompts and working material.

Using GPTHub AI:

The advertised approach is to choose from several models within one dashboard and complete different tasks in the same workspace.

For my testing, the second approach was convenient.

However, this doesn't automatically mean GPTHub AI is better than every dedicated AI platform.

Specialized applications may still offer stronger editing, integrations, image controls, or other advanced features.

I see GPTHub AI as a potential centralized workspace rather than a guaranteed replacement for every specialist tool.

Who Should Consider GPTHub AI?

Based on my experience, these are the people most likely to appreciate the concept.

Freelance writers: Useful for article outlines, first drafts, email sequences, and editing support.

Affiliate marketers: Can help prepare product descriptions, promotional emails, comparison content, and campaign ideas.

Content creators: Useful for generating scripts, content calendars, and social media variations.

Digital marketers: May help with advertising concepts, landing page copy, and promotional campaigns.

Researchers: The advertised long-context functionality may be particularly interesting for people handling lengthy reports and source material.

Small agency owners: Having different AI workflows in one interface could make repetitive production tasks easier to organize.

Beginners: The dashboard and prompt templates may provide a simpler starting point than building a complicated AI workflow from scratch.

Who Should Avoid GPTHub AI?

I wouldn't recommend purchasing it blindly if you fall into one of these categories.

• You expect every generated response to be perfect without editing.

• You require independently verified model specifications before purchasing.

• You need professional-grade image editing rather than basic generation.

• You require guaranteed enterprise integrations or custom development features.

• You expect AI to generate an immediate income without effort.

• You need a specific capability that hasn't been confirmed in the actual account.

It is important to match the platform to your real requirements.

Is GPTHub AI Legit or a Scam?

This is probably one of the most important questions people will ask before purchasing.

My five-day testing experience was positive. I generated content, summarized research material, prepared reports, created advertisements, and received useful coding assistance.

However, there are two separate things worth evaluating.

First, does the platform provide a functioning AI workspace that can help with practical assignments?

My recorded experience suggests that it did.

Second, are all the promotional claims about GPT-6 Astra, million-token capacity, premium-plan equivalence, future releases, and lifetime model availability independently established?

I cannot confirm all those claims through five days of use.

The offer itself identifies GPTHub AI as an independent platform and explicitly states that it is not affiliated with, endorsed by, or sponsored by OpenAI.

That distinction matters.

I would also recommend reviewing the actual checkout details, account terms, privacy information, and support arrangements before making a purchase.

My conclusion is that I found the workflow useful, but buyers should evaluate the advertised technical specifications separately from my personal experience.

GPTHub AI Frequently Asked Questions

1. What is GPTHub AI?

GPTHub AI is an all-in-one AI workspace advertised with multiple GPT models, content-generation features, long-context functionality, image generation, and ready-made prompts.

2. How much does GPTHub AI cost?

The introductory offer I reviewed displays a one-time price of $14.95. Prices may change, so check the current checkout page before purchasing.

3. Is GPTHub AI a monthly payment?

The advertised introductory package is presented as a one-time payment without recurring monthly charges. Check the actual purchase terms for any optional upgrades or additional charges.

4. Does GPTHub AI include GPT-6 Astra?

GPT-6 Astra is prominently advertised as part of the package. I recommend confirming the model availability and its exact capabilities inside the account.

5. Can beginners use GPTHub AI?

The platform is promoted as beginner-friendly. My initial dashboard exploration took approximately four minutes, and I didn't need technical knowledge for my basic writing tests.

6. Can I use GPTHub AI for freelance work?

The offer includes a commercial usage entitlement for freelance and client assignments. Review the actual license conditions before using generated material commercially.

7. Does GPTHub AI generate images?

Yes, the advertised package includes GPT Image 2.5 functionality. My initial test was suitable for a basic lead magnet visual, although premium creative work may require additional refinement.

8. Can GPTHub AI analyze large documents?

The offer promotes a one-million-token long-context mode. My five-day test included a 62-page research PDF and approximately 180 pages of material across three documents.

9. Does GPTHub AI require coding knowledge?

No coding knowledge was necessary for my initial tests. I also used the coding mode to troubleshoot a basic JavaScript issue.

10. Are there additional upgrades?

The offer mentions optional upgrades but does not provide a complete OTO price breakdown in the information I reviewed. Check the checkout sequence for current upgrade details.

11. Does GPTHub AI include future model updates?

The vendor advertises automatic additions of future GPT releases. I haven't tested this over a long enough period to independently confirm that promise.

12. Is there a money-back guarantee?

The promotional offer states that purchases are covered by a 30-day guarantee. Review the applicable terms and support instructions before purchasing.

My Final GPTHub AI Review Verdict: Is It Worth It?

After five days of testing, I can say that GPTHub AI gave me a positive experience for my regular freelance assignments.

The biggest advantage wasn't simply generating content faster.

It was having different model options available for different types of work.

I used Astra for detailed research and complex assignments, Luna for quicker variations, and Sol for more straightforward content tasks.

The long-document workflow was particularly interesting. My 62-page research summary took considerably less time than my usual approach, and the competitor analysis gave me a useful 47-page starting draft.

I also appreciated the prompt library, especially when working on repetitive content assignments.

There are still things I would like to test over a longer period.

I want to see how stable the platform remains, whether future model additions happen as advertised, and whether the image-generation capabilities improve enough for more demanding creative projects.

I would also avoid relying on its outputs without verification. I caught a pricing error during my research assignment, and that is exactly why human review remains important.

Would I purchase GPTHub AI again at the advertised $14.95 introductory price?

Based on my five-day experience, yes.

Would I claim that it replaces every premium AI platform or guarantees professional results without editing? No.

For freelancers, writers, marketers, and creators who regularly handle several types of AI assignments, the multi-model workspace is an interesting proposition.

The combination of content generation, research assistance, coding support, prompt templates, and image creation makes it worth examining.

My final recommendation is to consider the introductory package if its confirmed features match your requirements, review the actual purchase terms, and test the platform with your own assignments during the stated 30-day guarantee period.

My final score: 8.5/10 based on my five-day practical experience.

For me, the most valuable outcome was saving approximately 11.6 hours across five days.

That is the kind of practical improvement I look for when evaluating an AI tool.

GPTHub AI isn't magic, and it doesn't eliminate the need for experience or careful editing. But as a centralized AI workspace, it made my daily production process noticeably easier.

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If you're considering GPTHub AI, I would focus less on the extravagant promotional claims and more on whether its actual features can solve the repetitive tasks that consume your working hours.

I love blogs and social media, so I creat something interesting inside my social media website, it’s possible to create a personal blog.

When you post something in the social media, you can post this in your blog.

The blog can be acessed inside the social media, in the public timeline, so you will have readers.

And you can acesss externally using the public url.

Do you think that’s a good idea?

For example, I created the first blog:

https://historia.postandme.com

Its public, no login required, but for interaction it’s necessary to log in the social media.

BookBloom Review 2026 – My Real Experience After 5 Days of Testing

I recently tested BookBloom because I wanted to find a practical way to promote my Amazon KDP books without spending hours creating Pinterest graphics, writing captions, and figuring out what to publish every day.

After five days of using BookBloom, I had generated 180 promotional pins for two different books, published 21 of them, received 660 combined impressions, and recorded three actual book sales.

Those numbers aren't life-changing, but they gave me something I hadn't experienced with my books for quite some time: measurable activity from people who weren't friends or family.

In this BookBloom Review, I'll explain what happened during my testing, how the software works, what I liked, where I think it needs improvement, its pricing, included extras, and whether I believe it's worth considering for Amazon KDP authors.

I'm approaching this as an author who wants readers to discover existing books, not someone expecting an automated bestseller machine.

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What Is BookBloom?

BookBloom is an AI-powered promotional tool designed for Amazon KDP authors and self-publishers.

Its main purpose is straightforward: take one published book and turn it into a complete 30-day promotional campaign.

Instead of manually thinking of Pinterest topics, designing graphics, writing captions, and creating a publishing schedule, BookBloom brings those activities together inside one workspace.

You provide your Amazon book listing or basic book information, upload the cover, and let the software generate promotional ideas and materials.

The system can create:

• Pinterest promotional graphics.

• Different marketing angles for individual pins.

• Headlines, captions, and calls to action.

• Keyword-focused Pinterest content.

• A 30-day publishing calendar.

• A Pinterest profile and board blueprint.

• Individual landing pages for your books.

• Promotional opportunities through its Promotion Finder.

• Additional research and publishing resources.

One detail I appreciated immediately was that BookBloom wasn't restricted to fiction authors.

I tested it with a puzzle book and a cozy mystery. Both had different audiences, different promotional angles, and different reasons why somebody might want to purchase them.

The software handled both without requiring me to build two completely separate marketing systems.

Why I Decided to Try BookBloom

Before purchasing BookBloom, I had been dealing with a familiar problem.

My cozy mystery had been sitting around position #47 in its category for approximately three weeks. It had generated four sales, but two came from people I personally knew.

I had also been neglecting my puzzle book because I wasn't consistently promoting it.

I understood that publishing a book was only one part of the process. Getting readers to discover it was another challenge entirely.

I had considered Amazon Ads, but spending several dollars daily on advertising wasn't something I wanted to jump into without knowing whether the campaign would convert.

I had also tried creating Pinterest content manually.

The problem wasn't necessarily designing one graphic. It was deciding what to publish tomorrow, writing another caption, finding another angle, and repeating the process.

That became exhausting.

When I came across BookBloom, the $17 one-time introductory price caught my attention.

I wasn't expecting it to magically generate hundreds of sales. I simply wanted to see whether it could reduce the amount of repetitive promotional work I was doing.

I decided to test two books rather than judge everything from a single campaign.

My BookBloom Review: Five Days of Actual Testing

Here's how my experience unfolded.

Day 1: Getting Started and Creating My First Campaign

I started with the puzzle book because it felt like the safer option.

The initial setup took approximately 40 minutes, although I spent longer than necessary because I wanted to understand the available settings.

I pasted my Amazon listing, added the book cover, and entered a few details about the intended audience.

My description included phrases such as:

• Puzzle book for adults.

• Brain games.

• Large-print puzzles.

• Gift ideas for parents.

The AI key configuration took approximately six minutes in my case. The instructions themselves were straightforward, but I got distracted while following them.

Once the basic information was entered, I started the campaign generation process.

The actual build took less than five minutes.

What appeared next was something I hadn't previously experienced with my manual Pinterest workflow.

I had a complete 30-day calendar in front of me, with 90 planned promotional pieces.

That's three pieces per day.

I spent some time scrolling through the calendar and checking the generated captions.

Were all 90 perfect? Absolutely not.

I edited approximately 20 of the first 30 captions.

Some sounded slightly too promotional, while others needed a different opening line. I wanted the content to sound like something I would actually write.

Fortunately, BookBloom saved my edits. When I returned to those pieces, my rewritten lines were still there.

That was an important detail because I didn't want to repeat the same editing work.

My Day 1 results:

• Promotional pieces generated: 90.

• Captions edited: Approximately 20.

• Total time in the software: 41 minutes.

• Published pins: 0.

I deliberately didn't publish anything immediately. I wanted to review the campaign first.

Day 2: Publishing My First Pinterest Pins

On the second day, I returned to the calendar and selected three pins.

The publishing process was straightforward.

I opened a pin, downloaded the PNG graphic, copied its accompanying text, and uploaded everything to Pinterest.

Each pin took approximately two minutes to publish.

I didn't have to design anything from scratch or write another caption.

I also explored the landing-page builder.

BookBloom generated a page containing my book cover, description, Amazon link, and an email signup section.

I changed the headline because the original wording felt slightly too promotional for my audience.

The revised version was saved.

Later that evening, I entered my cozy mystery into the software.

Since I already understood the basic workflow, setting up the second campaign took approximately 15 minutes.

The interesting part was seeing how differently the system approached the two books.

The puzzle book needed visual and practical angles. The mystery needed genre-focused messaging and reader-interest hooks.

My Day 2 results:

Puzzle book:

• Published pins: 3.

• Impressions: 31.

• Outbound clicks: 2.

• Landing-page views: 4.

Cozy mystery:

• Published pins: 0.

Two outbound clicks might not sound impressive, but I was happy to see that somebody had actually moved beyond the Pinterest graphic.

Day 3: Discovering the Different Promotional Angles

Day three was when I started understanding the value of the campaign structure.

Initially, I assumed the 90 pins would simply be variations of the same promotional message.

That wasn't what I found.

For example, one puzzle-book graphic focused on large-print puzzles for people who prefer easier reading.

Another presented the book as a gift idea for parents.

A third showed an actual interior page.

These were three different reasons for someone to become interested in the same product.

That distinction matters.

Someone searching for a gift for their father might respond to a completely different message than someone specifically looking for brain games.

I published three additional puzzle-book pins and three cozy-mystery pins.

I also tested the Promotion Finder.

It provided approximately a dozen newsletter websites and author promotional opportunities that appeared relevant to my cozy mystery.

What I liked was that the eligibility questions were answered using information about my book rather than simply presenting a random collection of websites.

I submitted my book to four opportunities.

Two were still pending, one declined because it didn't accept series submissions, and one agreed to feature the book the following month.

Not every submission will work out, but having a starting list saved me time researching potential promotional opportunities.

My Day 3 results:

Puzzle book:

• Published pins: 6 cumulative.

• Daily impressions: 88.

• Outbound clicks: 5.

• Saves: 3.

Cozy mystery:

• Published pins: 3 cumulative.

• Daily impressions: 41.

• Outbound clicks: 2.

• Saves: 1.

Promotional submissions: 4.

There were still no sales at this point.

I think that's worth mentioning because clicks and sales are two different things. Getting someone to visit a book listing doesn't automatically mean they'll purchase it.

Day 4: My First Non-Family Sale

Day four was the most exciting part of my initial experiment.

I woke up and checked my KDP dashboard.

There was one puzzle-book sale.

I also noticed a Kindle Unlimited page-read notification for my cozy mystery.

Someone had borrowed the book and read approximately 60 pages.

I checked the tracking information and found that the puzzle-book sale appeared to be connected to a pin published on day two.

That particular pin used a gift-for-parents angle.

The cozy-mystery activity came from a promotional message aimed at readers looking for a series to binge.

These were not the first angles I would have thought of independently.

That made me appreciate the variety of promotional approaches more than the number of graphics generated.

Of course, one sale doesn't establish a reliable marketing channel. However, after weeks of limited activity, seeing a new reader arrive through Pinterest was encouraging.

My Day 4 results:

Puzzle book:

• Published pins: 9 cumulative.

• Daily impressions: 142.

• Outbound clicks: 9.

• Sales: 1.

Cozy mystery:

• Published pins: 6 cumulative.

• Daily impressions: 97.

• Outbound clicks: 6.

• KU page reads: 60.

Day 5: A More Consistent Publishing Routine

By the fifth day, the workflow was becoming familiar.

I published three more pins for each book and marked them as completed in the calendar.

This time, I spent approximately 12 minutes publishing the six pieces.

I didn't have to sit down and brainstorm six separate topics.

I simply reviewed the prepared content, downloaded the graphics, copied the captions, and published them.

The puzzle book recorded two additional sales: one paperback and one ebook.

My cozy mystery received another Kindle Unlimited borrow, generating approximately 140 additional page reads.

The important thing for me wasn't that the numbers had suddenly become enormous.

It was that I was finally following a repeatable promotional routine.

My Complete Five-Day BookBloom Results

Here's the combined picture after testing two books.

Total time invested: approximately 3 hours and 50 minutes.

I want to be completely clear about these results.

These are my reported five-day testing results, not a promise that another author will receive the same numbers.

The three sales came from the puzzle book. My cozy mystery generated reading activity but no confirmed sales during this initial experiment.

I also wouldn't use five days of Pinterest statistics to predict long-term performance.

The platform needs time to build meaningful visibility, and different genres can behave very differently.

Nevertheless, the experiment gave me a useful starting point.

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BookBloom Features: What Do You Actually Get?

After using the software, these are the main features I consider worth understanding before purchasing.

1. AI Promotion Strategist

This is the central part of BookBloom.

It takes information about your published book and generates multiple promotional angles.

Rather than producing 90 nearly identical advertisements, it approaches the book from different reader perspectives.

These include reader matching, practical information, curiosity, samples, gifts, and occasions.

I particularly liked this for my puzzle book because it gave me different ways to introduce the same product.

2. Pinterest Artwork Studio

The artwork studio lets you choose from different visual styles.

The available styles include:

• Clean Editorial.

• Cozy Lifestyle.

• Bold Graphic.

• Cinematic.

• Bright Illustrated.

You can preview the styles using your own cover before generating the graphics.

I found this useful because visual consistency matters when promoting multiple titles.

You can select three to five styles and create your promotional set in one pass.

3. AI Copywriter

The copywriter generates headlines, hooks, captions, calls to action, and relevant search phrases.

This was one of the most practical features during my experiment.

I still edited some captions, but having a starting point was considerably easier than staring at a blank screen.

Another positive detail was that my edits remained saved.

4. Thirty-Day Publishing Calendar

BookBloom creates a dated calendar containing the promotional pieces and their accompanying captions.

The campaign can contain three pieces daily, giving you 90 pieces across 30 days.

You can mark individual pieces as published and keep track of your progress.

For someone who struggles with consistency, this is a useful feature.

5. Pinterest Account Blueprint

The software also helps with the initial Pinterest profile structure.

It provides:

• Pinterest account name suggestions.

• Keyword-focused profile descriptions.

• Ten collection or board ideas.

• Individual keyword sets.

• A four-week starting plan.

• Profile and banner artwork.

This is particularly useful for authors who haven't previously built a Pinterest presence.

6. Individual Book Landing Pages

I liked having a separate page for each book.

The generated page can include your cover, book description, retailer links, sample content, promotional extras, and an email signup area.

You can edit the wording and monitor page views and clicks.

One important distinction: a landing-page visit is not the same as a completed purchase.

I appreciate that the tracking separates those activities instead of presenting every click as a sale.

7. Promotion Finder

This feature identifies promotional opportunities that may suit your book.

It can help locate relevant author websites, newsletters, and promotional spots.

The system also prepares submission materials based on your book information.

In my cozy-mystery experiment, this was useful because I didn't have to begin my research with a completely blank search page.

However, acceptance is still determined by the individual promotional website.

8. Book Content Engine

Another feature worth mentioning is the Book Content Engine.

You can upload a PDF or paste opening chapters.

BookBloom can use the actual book content to identify material worth featuring in promotions, such as samples, challenges, practical information, or bonuses.

This can make the resulting campaign more specific than one created using only a title and cover.

9. KDP Research

BookBloom also includes a research feature for exploring your genre.

It helps examine existing Amazon listings, formats, common characteristics, and possible title and keyword directions.

I see this as a useful starting point for authors planning future books or improving how existing titles are presented.

I wouldn't treat generated keyword suggestions as guaranteed ranking opportunities, though.

10. Optional Video Studio

The software also mentions an optional video-generation feature through BookBloom Pro.

It provides storyboards for promotional angles and vertical video creation.

The Pro description includes unlimited storyboards.

This is worth considering if you want to experiment with short-form promotional content alongside static Pinterest graphics.

However, I didn't use video creation during my five-day experiment, so I can't give a personal performance assessment of that feature.

BookBloom Pricing: How Much Does It Cost?

At the time of my purchase, the introductory price was $17 as a one-time payment.

This was the amount I paid for my initial testing.

The pricing presentation describes the purchase as including lifetime use without a recurring monthly software fee.

Here's how the included package is presented:

The displayed values are the seller's stated valuations, not independently verified market prices.

Another important detail is the AI configuration.

BookBloom uses your own AI provider key for content generation. You connect that key and pay the provider directly according to its pricing.

Therefore, although BookBloom itself is presented without a recurring monthly software fee, AI provider charges may still apply.

I recommend checking your AI provider's current pricing before generating large campaigns.

BookBloom Bundle and Included Extras

One of the things I wanted to understand before buying was whether the purchase included anything beyond the main Pinterest campaign builder.

There is an included training package called KDP AI CRACKED.

It is presented as training covering how to create books in different niches and promote them after publishing on Amazon KDP.

I consider this a useful addition for newer authors who want guidance beyond the promotional graphics themselves.

The overall package also brings together the campaign studio, Pinterest account blueprint, individual landing pages, and Promotion Finder.

What About BookBloom OTOs?

The pricing information I reviewed describes BookBloom Pro as an optional higher-tier offering.

The Pro description specifically mentions:

• Video Studio.

• Unlimited storyboards.

• One-click publishing to your own website.

I could not verify a separate OTO price or a complete upsell pricing schedule.

I therefore wouldn't give you an invented price or suggest that these features are included in the $17 purchase.

If you're considering an upgrade, check the current checkout and upgrade details carefully before making another purchase.

Pros and Cons of BookBloom

After five days of testing, here's my balanced assessment.

What I Liked

1. It reduces the content-planning workload.

I didn't have to decide what to publish every morning. The calendar was already prepared.

2. Multiple promotional angles.

The different approaches were more useful than simply generating dozens of variations of one advertisement.

3. Useful for different book genres.

I tested a puzzle book and a cozy mystery, and both produced relevant campaign ideas.

4. Simple publishing workflow.

Downloading a graphic, copying its caption, and uploading it to Pinterest was straightforward.

5. Saved edits.

I could rewrite captions without worrying about losing my changes.

6. Individual landing pages.

Having a separate destination for each book made the campaigns more organized.

7. Promotion Finder.

It helped me discover relevant promotional opportunities without starting from scratch.

8. No recurring BookBloom software fee in the advertised package.

The $17 introductory purchase was a relatively inexpensive way to test the workflow.

What I Didn't Like

1. Not every caption is ready to publish.

I edited approximately 20 of the first 30 captions. Personalizing the writing still takes effort.

2. Pinterest publishing requires manual involvement.

BookBloom prepares the campaign and export, but it doesn't automatically publish everything for you.

3. Your own AI key is required.

Beginners may need a little extra time to understand the configuration.

4. Five days isn't enough to evaluate long-term traffic.

My initial statistics were encouraging, but I need a longer testing period.

5. Sales aren't guaranteed.

A pin can receive impressions and clicks without generating a purchase.

6. Optional Pro features need separate consideration.

Authors interested in video creation or website publishing should verify the upgrade terms and pricing.

Who Should Consider BookBloom?

Based on the features and my testing, I think BookBloom is worth considering for several types of authors.

Amazon KDP beginners: If you've published your first book but don't know how to start promoting it, the calendar and account blueprint can provide structure.

Puzzle-book publishers: Puzzle books, activity books, and journals can benefit from promotional graphics showing actual interior pages.

Fiction authors: Cozy mysteries, romance, fantasy, and other genre-focused books can be introduced through reader-interest angles.

Nonfiction authors: Educational and how-to books can be promoted through practical questions and relevant topics.

Authors with multiple titles: The ability to create campaigns for multiple books makes the workflow interesting for people managing an existing catalogue.

I also think it may suit authors who already understand Pinterest but struggle to produce content consistently.

Who Should Avoid BookBloom?

I wouldn't recommend purchasing it with unrealistic expectations.

If you expect software to publish everything automatically and produce guaranteed daily sales, this probably isn't what you're looking for.

It's also not a replacement for writing a good book, improving your cover, researching your audience, or presenting an accurate Amazon listing.

Authors who don't want to use Pinterest or create promotional content may not benefit much from the main workflow.

And if you aren't comfortable configuring your own AI key, be prepared to spend some time learning that initial step.

Frequently Asked Questions About BookBloom

1. What is BookBloom used for?

BookBloom helps Amazon KDP authors create promotional campaigns for their published books. It generates Pinterest graphics, captions, promotional angles, calendars, landing pages, and other marketing resources.

2. Is BookBloom suitable for beginners?

Yes. The guided workflow and Pinterest account blueprint make it approachable for beginners. However, first-time users may need a little time to configure their AI provider key.

3. Does BookBloom automatically publish Pinterest pins?

No. It prepares the promotional content and provides an export that Pinterest can import. You retain control over when your content is published.

4. How many pins can BookBloom generate?

The advertised campaign structure includes up to 90 promotional pieces over 30 days, with three pieces planned per day.

5. Can I promote more than one book?

Yes. The product presentation describes support for up to ten books at once. I personally tested two separate books during my initial experiment.

6. Does BookBloom work for puzzle books?

My experience suggests that it can be useful for puzzle books. I particularly liked the ability to use interior-page visuals and different gift-oriented promotional angles.

7. Does it work for fiction authors?

Yes. I tested it with a cozy mystery and received genre-oriented promotional ideas, including a series-focused angle.

8. Does BookBloom guarantee sales?

No software can guarantee that people will purchase your book. My five-day experiment produced three puzzle-book sales, but those results should not be treated as a typical outcome.

9. Do I need an AI API key?

Yes. BookBloom uses your own AI provider key for generation. Provider charges may apply separately.

10. Is there a monthly fee?

The advertised $17 package is presented as a one-time purchase without a recurring BookBloom software fee. Separate AI provider charges may apply.

11. What is included in KDP AI CRACKED?

It is included training covering book creation in different niches and methods for promoting published books on Amazon KDP.

12. Does BookBloom include landing pages?

Yes. It can create individual pages for your books, with cover artwork, descriptions, retailer links, and an email signup option.

13. Can I edit generated captions?

Yes. You can edit headlines, captions, and other promotional wording. During my test, my changes remained saved when I returned to the campaign.

14. Is BookBloom Pro included?

The main package and Pro features should be distinguished. Video Studio and one-click publishing to your own website are described as Pro features. Check the current upgrade terms for exact pricing.

15. Is BookBloom worth $17?

Based on my five-day experience, I think the introductory price is reasonable for authors who want help preparing a month of promotional content. However, the value depends on whether you'll actually publish the content and use the available features.

My Final BookBloom Review Verdict: Is It Worth It?

After five days, I have a much clearer opinion about BookBloom.

I purchased it because I was tired of publishing books and then watching them sit without much reader activity.

I wanted a repeatable way to promote my existing titles without spending every evening thinking of new graphics, captions, and Pinterest topics.

The software helped me with exactly that part.

I generated 180 promotional pieces across two books, published 21 pins, received 660 combined impressions, recorded 37 outbound clicks, and generated three puzzle-book sales.

My cozy mystery also received 200 Kindle Unlimited page reads.

Are these enormous results? No.

Would I call five days enough to establish long-term profitability? Definitely not.

But the experiment gave me something valuable: a practical starting point and a promotional routine I could realistically continue.

The feature I appreciated most wasn't the artwork generator or even the AI copywriter.

It was the combination of different promotional angles and a prepared publishing calendar.

I no longer had to wake up wondering what I should post that day.

There is still work involved. I needed to edit captions, publish the pins myself, check the statistics, and submit promotional applications. BookBloom doesn't eliminate the need to understand your readers.

However, it reduced the amount of repetitive preparation I had to do.

Would I purchase BookBloom again for $17? Yes.

I would also like to continue testing the campaigns over the next 25 days before making any stronger claims about its long-term performance.

If you're an Amazon KDP author with published books that aren't receiving the attention you hoped for, BookBloom is worth investigating.

Just remember that it provides a promotional workflow, not guaranteed sales.

For me, the biggest improvement was finally having a system that made promoting my books feel manageable rather than another unfinished task on my to-do list.

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That's why, based on my initial experience, I consider BookBloom a useful tool for KDP authors who want to become more consistent with Pinterest promotion. Thanks For Reading.

My apology for the title misspelling...my father told me to never make the same mistake twice. So I will make sure I don't misspell it again...lol. However, I once read that the Native Americans stated if we make a mistake, that only means that we are human. I'm not trying to justify myself, or maybe slightly. Thank you again to all that take time to read my blogs.

I wrote this poem, but I don't remember when. I usually date all my poems, but forgot this one. "Wake Up World" It's all around you and me. Open your eyes so you can see. They are stealing innocent women and girls, to sell them around the world. Billions of dollars for innocent lives. Forced into slavery through filthy lies. They call it trafficking, but it's nothing new. It's really ancient slavery, and evil abduction too. They shove the innocents into dirty semi-trucks...to sell them for millions of bucks. This is a terrible crime, that's way out of hand. Girls in strange boats, in the dark of night, traveling no where with evil monsters creating fright. Oppressors practicing under the sun. They are preying on anyone. King Solomon wrote the book of Ecclesiastes in the Old Testament of the KJV of the Bible. It seems he experienced some pretty wicked accounts back then. For this particular verse indicates that. "I saw all the oppressions that are practiced under the sun. Look, the tears of the oppressed-with no one to comfort them! On the side of the oppressors there was power. Ecclesiastes 4:1 I feel sick within thinking about, especially the kids, what they are forced to act upon, what they are being forced to do for the sake of the filthy almighty dollar. These fools are playing a dirty game so they can fill their pockets with something, they don't realize at the moment, they cannot take with them when they finally take their last hellish breath. I truly hope that the content of my blogging makes every reader angry. Anger is not a negative emotion when it comes to forced sex committed against anyone. Righteous indignation is not about a personal vendetta. It's a stance that morally caring people take against evil. It's an anger that aligns with truth and justice. Are you angry that our children are being wasted? Are you angry that our children are being tortured? Are you angry that our children are missing, and Mommies and Daddies are scared and worried not knowing if they will ever see their kids again? You may feel helpless, like there is nothing you can do. But for those who believe that prayers get answered...well that's the best thing that you can do. And if you don't believe in praying, you can send out positive thoughts everyday. It's dead certain that all those who have been abducted do want someone to step forward to help them escape from the dark-bloody-wickedness that they have been swallowed up into. This is an analogy of numbers: Imagine if just one-hundred-thousand people were either praying the same prayer, or thinking the same positive thoughts at the same time...the power that could be generated would be impressive. If you toss a rope with just a couple of strands to someone drowning, more than likely, it will break. But if you toss a rope with multiple strands to someone drowning, then there is a great possibility you may save that person from drowning. I'm just saying there is power in numbers.

That is all, just celebrating (^^).

Hi everyone,

I had read Klara and the sun, and then I wrote about my opinions and what I had concluded. So, I will appreciate knowing your feedbacks and thanks.

https://krimech-anas.blogspot.com/2026/11/blog-post-container.html

My Honest NAZO BOX Review After 30 Days of Testing

I spent 30 days testing NAZO BOX, a puzzle-creation tool designed to turn picture-logic puzzles into complete murder mystery activity books for Amazon KDP. I wanted to find out whether NAZO BOX could genuinely help someone without graphic design experience or puzzle-making skills create publishable books.

I received review access from the vendor before its official November 23, 2026 launch. Rather than judging it from its promotional claims, I focused on the actual creation process, editing options, puzzle verification, PDF exports, publishing workflow, and the results from my first month.

By the end of my 30-day experiment, I had published five books, generated approximately 280 verified puzzles, recorded 56 sales, and earned $131.25 in royalties.

Those numbers surprised me, although they certainly don't mean everyone will achieve similar results. There was still plenty of work involved, particularly with covers, product descriptions, keyword research, and publishing.

Here is everything I discovered.

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What Is NAZO BOX?

NAZO BOX is a puzzle-book creation application that specializes in murder mystery nonogram books.

If you've never encountered a nonogram before, it's a picture-logic puzzle where numbers along the rows and columns tell you which squares to fill. As you solve the grid, a hidden picture gradually appears.

NAZO BOX takes that familiar puzzle format and combines it with short murder mystery scenarios.

Instead of simply completing a random picture, readers work through a fictional crime case. They solve the puzzle, uncover visual evidence, and use the resulting picture as part of the mystery.

The interesting part is how the software handles production.

It generates the puzzle, calculates its numerical clues, verifies that the puzzle has exactly one solution, and places the finished activity into a book layout.

You can then edit the text, change pictures, adjust page elements, add extra pages, and export the finished project.

The main idea is to make creating picture-logic mystery books considerably easier for people who don't have the technical skills to construct these puzzles manually.

It supports:

• Murder mystery nonogram creation.

• Automatic puzzle generation and verification.

• Multiple difficulty settings.

• Different page layouts and sizes.

• Editable titles, text, and pictures.

• Drag-and-resize page editing.

• Custom notes, image, and blank pages.

• Project saving and reopening.

• PNG and JPG page exports.

• Print-ready PDF exports.

• Commercial rights to books created with the software.

NAZO BOX works on Mac and PC, according to the vendor's product information.

Why I Decided to Test NAZO BOX

Before trying this software, I had already experimented with low-content publishing.

I created a couple of word-search books and a journal. The problem wasn't necessarily creating the books. It was getting them noticed.

There were so many similar products that mine struggled to gain visibility. I could spend an entire evening creating something, upload it to Amazon, and then see practically no movement.

I started looking for something different.

That's when I became interested in murder mystery puzzle books, particularly the nonogram format.

I liked the idea because it combines two activities: solving puzzles and following a story. It also gives creators more room to experiment with themes and series.

However, creating nonograms manually looked complicated.

I would need to design the picture, calculate the numerical clues, verify the solution, write the accompanying mystery, and arrange everything into a printable layout.

That was a lot of work for someone without design or puzzle-development experience.

NAZO BOX caught my attention because it promised to handle the technically difficult parts.

I received a review copy from the vendor and decided to run a proper 30-day experiment.

My goal was straightforward: create actual books, upload them to KDP, and see whether the production process was practical enough to repeat.

My 30-Day NAZO BOX Experience

Week 1: Learning the Software and Creating My First Books

Day 1–2: Installation and Initial Setup

My first task was getting familiar with the interface.

I started with the included training videos, which took approximately 40 minutes to complete.

I appreciated that the training wasn't unnecessarily complicated. It introduced the main features and showed how to move through the creation process.

I still needed approximately an hour to become comfortable with the interface.

I decided not to start with complicated projects.

Instead, I selected the easy difficulty setting, chose a one-case-per-page layout, and clicked Build Book.

The software generated 12 cases while I was away preparing something to eat.

That was my first positive experience with NAZO BOX.

I wasn't manually drawing pictures or calculating the numerical clues. The application handled those steps.

Day 3: My First Editing Session

Generating a book was one thing. Making it look like something I would actually publish was another.

I spent this session changing the detective's name, rewriting a couple of case introductions, and adjusting the title page.

The drag-and-resize functionality took a little practice.

I occasionally moved elements incorrectly or needed another attempt to position something properly.

However, once I understood how the editing controls worked, the process became considerably easier.

By the end of the session, I had a draft that looked presentable.

Day 4–5: Testing the PDF Export

This was probably the most important part of my first week.

One of my biggest concerns was whether the exported book would have formatting problems.

Anyone who has prepared an interior for Amazon KDP knows that incorrect margins, misplaced elements, and inconsistent page dimensions can create unnecessary headaches.

I exported my first book as a PDF and checked the pages before uploading.

The result was encouraging.

My first KDP upload was accepted without a formatting flag.

That gave me confidence to continue.

Day 6–7: Building a Larger Book

After completing the first project, I decided to test a more ambitious layout.

This time, I selected harder puzzles and created a 60-case book.

Including my editing work, the complete process took approximately three hours.

That was the moment I started understanding the practical value of NAZO BOX.

I wasn't spending hours creating individual puzzles anymore. I could concentrate on improving the actual book.

Week 1 Results:

• Draft books created: 2

• Total time spent: Approximately 9 hours

• Puzzles generated and verified: 72

• Puzzles requiring manual correction: 0

• First KDP upload: Accepted on Day 5

Week 2: Publishing My First Books

Day 8: Publishing Book One

My first published title was:

The Locked Study: 50 Picture-Logic Murder Mysteries.

I created the cover using Canva.

I wanted something dark and straightforward that communicated the murder mystery theme immediately.

The cover took approximately 30 minutes.

I then prepared the listing and uploaded the finished interior.

Day 9–10: Waiting for the First Sale

Nothing particularly exciting happened during these two days.

I checked the KDP dashboard more frequently than I probably should have.

There were no immediate sales, and I started wondering whether the niche was going to work for my books.

I reminded myself that publishing a book doesn't automatically bring readers.

The cover, title, description, keywords, and overall presentation all matter.

Day 11: My First Sale

I finally recorded my first sale.

It was only one copy, but it was a satisfying moment.

I had gone from experimenting with software to having someone purchase an actual book I created.

Day 12–14: Publishing Book Two

My second book was titled:

Deadly Evidence: 60 Cases.

During this period, I also started working on the listings.

This was an important lesson.

NAZO BOX helps create the actual product, but it doesn't eliminate the need to understand Amazon KDP publishing.

I used the included KDP Keyword Finder bonus to research relevant phrases and revised my title and all seven keyword fields.

After making those changes, I started noticing an improvement in organic impressions.

I can't attribute every change to one tool, but the keyword work made me realize how important proper listing preparation is.

Week 2 Results:

• Books published: 2

• Units sold: 6

• Royalties: $14.20

• Reviews received: 1

• Time spent on covers and listings: Approximately 7 hours

Week 3: Testing the Difficulty-Ladder Strategy

This was probably my most interesting week.

Instead of creating another unrelated puzzle book, I decided to experiment with a series.

My first book contained easier puzzles, while my second included harder cases.

I created a medium-difficulty volume to sit between them.

The idea was simple:

A reader who enjoyed the first book would have another natural option to explore.

I also connected the listings where appropriate and monitored their performance.

I noticed that the medium book started receiving attention alongside the earlier titles. I also saw activity consistent with readers discovering related books through Amazon's recommendation areas.

I wouldn't claim that this strategy guarantees repeat purchases, but it gave me a more organized publishing direction.

Testing Full-Colour Books

I also experimented with the full-colour option.

The software allowed me to switch the book to colour with one click.

I used that functionality to create a small seasonal mystery based around a snowed-in lodge.

I wanted to see whether the same underlying creation process could support different visual presentations.

It worked well for my experiment.

One Mistake I Made

I did run into a small problem.

I tried adding a notes page and an image page to the front matter but placed them in the wrong order.

I ended up rebuilding the book.

It cost me approximately 45 minutes.

This wasn't a software malfunction. I simply rushed the page arrangement without checking the order first.

My advice is to plan your front matter before adding the final pages.

Week 3 Results:

• Books published cumulatively: 4

• Units sold during the week: 19

• Weekly royalties: $44.65

• Total reviews: 4

• Broken-puzzle complaints: 0

• Time spent: Approximately 8 hours

Week 4: Creating More Books and Reviewing Results

By the fourth week, I was much more comfortable with the application.

The medium-difficulty book started generating sales, and the earlier titles continued receiving occasional purchases.

I decided to create a fifth book.

This time, I experimented with a gift edition featuring a custom detective name.

I genuinely liked this feature because it gave me another way to differentiate the finished product.

I also reopened two earlier projects from my saved library.

Rather than starting again, I adjusted their difficulty settings and prepared fresh versions.

This is where the project library became particularly useful.

Being able to save a project, return to it later, make changes, and export another version saved me unnecessary repetitive work.

By Day 30, I had five published books and two additional drafts ready for future development.

Week 4 Results:

• Books published cumulatively: 5

• Units sold during the week: 31

• Weekly royalties: $72.40

• Total reviews: 7

• Average review rating: 4.6 stars

• Time spent: Approximately 9 hours

My Complete NAZO BOX 30-Day Results

Here is the complete picture after my first month.

<small>These are my reported results from this individual 30-day experiment, not independently audited figures or a projection of what another purchaser will earn.</small>

The number that surprised me most wasn't the royalty total.

It was the combination of five published books and approximately 280 verified puzzles without having to manually repair a puzzle.

In my earlier word-search experiments, I was always concerned about mistakes slipping through.

With NAZO BOX, the automated verification process removed much of that particular production concern.

The $131.25 was encouraging, but I don't want to exaggerate it.

This wasn't a life-changing result. It was a modest first-month outcome that gave me something tangible to build upon.

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NAZO BOX Features: What Do You Actually Get?

Now that I've explained my experience, let's look more closely at the main features.

1. Verified Picture-Logic Engine

This is the central feature of NAZO BOX.

The application generates a picture-based logic puzzle, calculates its numerical clues, and checks whether the puzzle has exactly one valid solution.

This matters because an incorrectly constructed nonogram can frustrate readers.

Imagine completing a grid only to discover that the clues don't produce a unique answer.

That would be a poor experience for someone who purchased the book.

According to the vendor, puzzles that fail the verification process aren't included in the finished output.

During my 30-day test, I generated approximately 280 puzzles and didn't encounter one that required manual correction.

2. Multiple Difficulty Settings

Not every reader wants the same challenge.

Some prefer simple puzzles that can be completed quickly, while others enjoy larger and more complicated grids.

NAZO BOX includes different difficulty settings.

I used this functionality to create easy, medium, and harder books.

It also makes creating a progressive series more practical.

3. Flexible Page Layouts

You can choose different layouts depending on how you want the finished book organized.

For example, you can create a one-case-per-page format or experiment with alternative arrangements.

This is useful when developing books for different audiences.

4. Edit Titles, Text, and Pictures

The generated content doesn't have to remain exactly as it appears initially.

You can change titles, descriptions, pictures, and other page elements.

I used this to personalize the detective names and rewrite some of the case introductions.

This is important because I wouldn't recommend publishing generated material without reviewing it.

A little customization can make the finished book feel more cohesive.

5. Drag, Resize, and Format Elements

NAZO BOX includes editing functionality for arranging the contents of individual pages.

You can move elements, resize them, and adjust their presentation.

I needed a little time to understand this feature, but it became easier after a few editing sessions.

6. Add Custom Pages

Another useful feature is the ability to add pages beyond the generated puzzle content.

The available options include:

• Text pages.

• Image pages.

• Notes pages.

• Blank pages.

This allows you to create introductory instructions, additional notes, or other supporting material.

7. Save and Reopen Projects

The local book library was one of my favourite features.

You can save projects and return to them later.

This became particularly useful when I started experimenting with different difficulty levels.

Instead of recreating everything, I could reopen an existing project and continue editing.

8. PNG and JPG Exports

The software can export individual pages as PNG and JPG images.

These files can be useful for Etsy product previews, promotional graphics, and other presentation materials.

9. Print-Ready PDF Export

For Amazon KDP creators, PDF export is particularly important.

NAZO BOX provides print-ready PDF exports, with the advertised plan allowing up to 100 PDF exports per month.

My first KDP upload was accepted without a formatting flag.

However, I still recommend checking the exported file carefully before publishing. Always confirm that the page dimensions, margins, page order, and final interior meet the current requirements of your chosen publishing platform.

How to Create a Book Using NAZO BOX

One thing I appreciated was that the overall creation process was relatively straightforward.

You can break it into three main stages.

Step 1: Create Your Book

Open NAZO BOX and select the difficulty level, page size, and layout.

Choose the type of book you want to create and click Build Book.

The application generates the puzzles and organizes them into the selected format.

Step 2: Edit and Personalize

Once the initial book is ready, review the pages.

Change titles, modify story text, replace pictures, and adjust the layout.

You can also add introductory pages, notes, images, and blank pages.

I recommend spending enough time here to make sure the book has a consistent presentation.

Step 3: Export and Publish

Save your project in the library.

Export the finished book as a PDF for print publishing or use PNG and JPG exports when you need individual page images.

Before uploading to Amazon KDP, inspect the complete interior and prepare your cover and listing separately.

That's essentially the workflow I followed throughout my experiment.

What Types of Books Can You Create?

One advantage of NAZO BOX is that the same basic puzzle engine can support different publishing ideas.

Here are six directions I found interesting.

1. Classic Murder Mystery Puzzle Books

Create themed collections featuring fictional crimes, suspects, evidence, and picture-logic challenges.

2. Large-Print Mystery Books

Use larger grids and a more spacious presentation for readers who prefer less crowded pages.

3. Difficulty-Ladder Series

Create an easy first volume, a medium second volume, and a harder third volume.

This was one of my favourite approaches because it gives readers a reason to explore additional titles.

4. Holiday and Seasonal Mysteries

Create themed collections around Halloween, winter holidays, or other seasonal occasions.

My snowed-in lodge experiment was an example.

5. Travel and Activity Books

Develop smaller puzzle collections intended for travel, waiting rooms, or general entertainment.

6. Gift and Custom Editions

Experiment with personalized detective names and themed editions.

I tested this approach with my fifth book.

The important thing is not to publish six variations of essentially identical content without thinking about the reader.

Each title should have a clear purpose and a reason to exist.

NAZO BOX Bonuses: What Is Included?

The vendor is advertising five launch bonuses alongside the main application.

These are browser-based tools rather than ordinary PDF guides.

Here is what is included.

Bonus 1: PDF Page Mover

<small>Vendor-stated value: $97</small>

This tool lets you reorder, remove, or merge pages in a PDF through your browser.

It can be useful when you discover that the front matter or back matter needs rearranging after exporting a book.

I particularly liked the idea of having a separate utility for correcting page order without opening a full design application.

Bonus 2: KDP Keyword Finder

<small>Vendor-stated value: $197</small>

This tool is intended to help identify phrases Amazon buyers search for.

It can help with:

• Book title research.

• Keyword selection.

• Amazon listing preparation.

• Understanding how readers describe the products they're looking for.

I used this bonus during my second week when revising my book listings.

Bonus 3: Description Helper

<small>Vendor-stated value: $97</small>

This utility helps generate formatted product descriptions from information about your book.

It's potentially useful when you're preparing multiple listings.

However, I would still review and personalize the final description instead of publishing the generated text without checking it.

Bonus 4: QR Book Generator

<small>Vendor-stated value: $47</small>

The QR Book Generator lets you add QR codes to your pages.

The vendor describes uses such as scan-to-solve and scan-for-answers experiences.

This could provide another way to make puzzle books more interactive.

Bonus 5: Best Amazon KDP Research Tool and Niche Revealer

<small>Vendor-stated value: $197</small>

This tool is designed to help creators examine what's selling, identify crowded categories, and look for potential gaps.

I consider research an important part of publishing because creating a book without understanding its intended audience can lead to wasted effort.

The five bonuses have a combined vendor-stated value of $635.

Launch availability: The vendor advertises these five tools as launch-window bonuses, with availability tied to its promotional period. Confirm their inclusion at checkout before purchasing.

NAZO BOX Pricing: How Much Does It Cost?

One important detail: I received review access from the vendor, so I didn't independently complete a retail purchase at the launch checkout price.

The promotional material describes NAZO BOX as a one-time-payment product.

According to the vendor:

• There are no recurring fees on the advertised plan.

• The software works on Mac and PC.

• Support is included.

• The plan includes up to 100 PDF exports per month.

• Full commercial rights are included for books created with the software.

The exact launch checkout amount wasn't specified in the product information I reviewed, so I won't invent a price.

If you're considering purchasing, check the official checkout page on November 23, 2026, for the confirmed price.

NAZO BOX OTO Pricing

I couldn't verify a separate list of optional upgrades or their prices from the supplied product information.

I therefore wouldn't give you invented OTO names or prices.

My recommendation is to examine the checkout carefully and check whether any additional products are offered separately.

For my evaluation, the main product and its advertised features were the focus.

NAZO BOX Pros and Cons

After 30 days, these are the advantages and disadvantages I would consider before purchasing.

Pros

1. Automated Puzzle Creation

The software handles the technical process of generating picture-logic puzzles.

2. Built-In Puzzle Verification

Its main engine checks puzzles for a single valid solution. This was particularly important in my experiment.

3. Faster Book Production

I created five published books in approximately 33 working hours.

4. No Graphic Design Background Required

You don't need to manually draw every puzzle or construct the numerical clues.

5. Flexible Editing

Titles, text, pictures, and page elements can be modified.

6. Multiple Difficulty Levels

Useful for creating collections and progressive puzzle series.

7. Full-Colour Option

You can experiment with colour editions without rebuilding every page manually.

8. Saved Project Library

You can reopen and revise previous projects.

9. Multiple Export Formats

PNG, JPG, and PDF exports provide flexibility.

10. No Recurring Fees on the Advertised Plan

The vendor describes the main offer as a one-time payment.

11. Commercial Rights

The vendor states that creators receive commercial rights to the books they make.

12. Training and Support

Training videos and support from the creators are included according to the offer.

Cons

1. There Is Still a Learning Curve

Although the main process is straightforward, the editing controls require practice.

2. Covers Are Your Responsibility

I used Canva to create my covers. NAZO BOX doesn't eliminate this part of the publishing process.

3. Listings Need Individual Attention

You still need to write descriptions, select keywords, and prepare your Amazon listings.

4. Publishing Doesn't Guarantee Sales

The software creates books. It doesn't guarantee readers, rankings, or royalties.

5. Page Ordering Requires Attention

My front-matter mistake cost me approximately 45 minutes.

6. PDF Export Allowance

The advertised plan specifies up to 100 PDF exports per month. Creators who regularly produce large numbers of revised editions should consider this allowance.

7. The Niche Could Become More Competitive

A relatively new category can attract more creators over time. Early entry doesn't guarantee a permanent advantage.

Is NAZO BOX Beginner-Friendly?

I would say yes, particularly if you're interested in creating puzzle books but don't have the technical skills to build nonograms manually.

My own experience is a good example.

I started without knowing how to calculate nonogram clues or construct verified picture-logic puzzles.

During the first two days, I was still learning the interface.

By the end of the first week, I had created two drafts and successfully uploaded my first book.

The most important distinction is that beginner-friendly doesn't mean completely effortless.

You still need to learn how to:

• Select an appropriate book concept.

• Review the generated pages.

• Arrange the interior.

• Create an attractive cover.

• Prepare a product listing.

• Research relevant keywords.

• Understand KDP publishing requirements.

If you're prepared to learn those steps, NAZO BOX can remove a substantial part of the technical production work.

NAZO BOX vs. Creating Puzzle Books Manually

Before testing this application, I assumed manual puzzle creation would be the more flexible approach.

However, the time difference became apparent.

When creating a nonogram manually, you have to design the picture, calculate the row and column clues, verify the solution, and arrange the final pages.

A single mistake can affect the entire puzzle.

With NAZO BOX, much of that process is automated.

You choose the settings, generate the book, review the output, and personalize it.

The biggest difference isn't simply speed.

It's the ability to repeat the production process without having to reconstruct every puzzle from scratch.

That said, manual creation still offers greater freedom if you want to design every visual element yourself.

NAZO BOX is more suitable for creators who value a structured workflow and want to produce books in this particular puzzle category.

Is NAZO BOX Worth It?

This is probably the question most people reading a NAZO BOX review want answered.

My opinion after 30 days is positive, but there are some conditions.

I think the application has genuine value for someone who wants to create murder mystery nonogram books without spending hours constructing puzzles manually.

The verified puzzle engine is its biggest advantage.

The ability to edit pages, save projects, change difficulty levels, and export finished interiors makes the overall process more practical.

My own results were encouraging.

Five books, 56 sales, and $131.25 in royalties during the first month gave me a reason to continue.

But I wouldn't recommend purchasing it purely because of those figures.

My results involved approximately 33 hours of work, including publishing preparation.

I also created my covers, worked on my listings, and researched keywords.

The software helped me produce the books. It didn't do all the work involved in getting them noticed.

For someone who enjoys creating activity books and is willing to learn publishing, I think the concept is worth considering.

For someone expecting automatic royalties without creating or promoting anything, it probably isn't the right choice.

Frequently Asked Questions About NAZO BOX

1. What is NAZO BOX used for?

NAZO BOX is used to create murder mystery nonogram books. It generates picture-logic puzzles, verifies their solutions, organizes them into book layouts, and provides editing and export functionality.

2. Do I need puzzle-making experience?

No previous nonogram experience is required according to the vendor. The application automates puzzle generation and verification. You will still need to learn the interface and review your finished books.

3. Do I need graphic design skills?

You don't need to manually draw the puzzles. NAZO BOX includes page editing and formatting tools. However, you may still want an external design application for creating professional covers and promotional graphics.

4. Are the puzzles automatically verified?

The vendor states that its picture-logic engine checks puzzles to confirm that each has exactly one solution.

In my 30-day experiment, approximately 280 generated puzzles required no manual corrections.

5. Can I sell books created with NAZO BOX?

According to the vendor, the product includes full commercial rights to books created with the application.

It states that you can sell your creations through Amazon KDP, Etsy, Gumroad, your own website, or physical sales channels.

Always review the applicable publishing platform's rules before uploading.

6. Does NAZO BOX work with Amazon KDP?

Yes. The vendor provides print-ready PDF exports intended for KDP publishing.

My first PDF upload was accepted without a formatting flag.

You should still inspect your own exported files before publishing.

7. What export formats are available?

The advertised formats include PNG, JPG, and PDF.

PNG and JPG are useful for individual pages and promotional images, while PDF is intended for complete print interiors.

8. How many PDF exports can I make?

The advertised plan includes up to 100 PDF exports per month.

9. Can I edit a generated book?

Yes. You can edit titles, story text, pictures, and page elements. You can also move, resize, and format different components.

10. Can I create different difficulty levels?

Yes. The software includes difficulty controls that let you create easier and more challenging puzzle collections.

11. Does NAZO BOX have recurring fees?

The vendor advertises the main offer as a one-time payment without recurring fees.

Check the final checkout details to confirm the terms of the offer you're purchasing.

12. Does NAZO BOX work on Mac?

The vendor states that the application works on both Mac and PC.

13. Is customer support included?

Yes. The offer includes training videos and support from the creators, Ike Paz and Luke Bowes.

During my experiment, I emailed Ike about a page-ordering question on Day 16 and received a reply the same day.

14. Is there a money-back guarantee?

The vendor's promotional information states that all sales are final.

There is no advertised money-back guarantee in the information I reviewed. Make sure you are comfortable with the purchase terms before proceeding.

15. When does NAZO BOX launch?

The official launch date provided by the vendor is November 23, 2026.

The review copy I tested was provided before the public launch.

16. Will NAZO BOX automatically generate royalties?

No. It creates puzzle books, but it doesn't guarantee sales or royalties.

You remain responsible for covers, listings, publishing decisions, audience research, and ongoing improvements.

Who Should Consider NAZO BOX?

Based on my experience, I would put the following groups on my potential buyer list.

Beginner KDP Publishers: People who want to explore puzzle books without learning how to construct nonograms manually.

Existing Activity Book Creators: Publishers interested in adding picture-logic mystery books to their catalogues.

Puzzle Enthusiasts: People who enjoy nonograms and want to create themed collections.

Etsy Digital Product Creators: Sellers who want to explore individual puzzle-page graphics and related printable products, subject to the relevant platform requirements.

Series Publishers: Creators who want to experiment with easy, medium, and difficult editions rather than repeatedly publishing unrelated books.

Who Should Avoid NAZO BOX?

I would think twice about purchasing if:

• You expect guaranteed royalties.

• You don't intend to create or publish any books.

• You want every page to be individually illustrated by a professional artist.

• You dislike editing and reviewing generated content.

• You need complete creative freedom over every technical aspect of puzzle construction.

• You aren't comfortable with the vendor's final-sale purchase terms.

This is a specialized creation application, not a shortcut around the work involved in publishing.

My Final NAZO BOX Review Verdict

After spending 30 days working with NAZO BOX, I can say that it made creating murder mystery nonogram books much more manageable than I expected.

The biggest advantage for me was the verified picture-logic engine.

I didn't have to spend hours drawing grids, calculating clues, and worrying about whether a puzzle had multiple possible answers.

I could generate a book, review the pages, make adjustments, and prepare the finished interior for publishing.

The editing controls took some getting used to, and I still had to handle covers, listings, and keyword research myself.

But the overall workflow became noticeably easier after the first few sessions.

My final first-month results were five published books, approximately 280 generated and verified puzzles, 56 units sold, and $131.25 in royalties.

I'm not presenting those figures as a promise of what someone else will achieve. They're simply the outcome of my own experiment.

What matters more to me is that I now have five published titles and two additional drafts that I can continue developing.

I started this experiment without much experience creating picture-logic puzzles. Thirty days later, I had a repeatable process for producing them.

Would I recommend NAZO BOX?

Yes, for the right person.

If you're interested in Amazon KDP puzzle books, murder mystery activity books, and nonogram publishing, NAZO BOX is worth examining.

Its combination of automatic puzzle verification, book creation, editing tools, and export options addresses a genuine production problem.

Just remember that creating a good book and getting people to buy it are two different challenges.

I see NAZO BOX as a tool that helps with the first challenge, while leaving the second in your hands.

With its official launch scheduled for November 23, 2026, I would recommend checking the final launch price, included bonuses, and purchase terms before making a decision.

For my experiment, it delivered something I was looking for: a way to create more puzzle books without spending most of my time on the technical work.

And that's why I consider my 30-day experience a positive one.

👉Get Nazo Box Today with Best Offer and Premium Bonus ✅

Review Disclosure: I received NAZO BOX review access from the vendor before its official November 23, 2026 launch. The experience and performance figures described above are based on my individual 30-day testing log. I have shared both the positive results and the practical limitations. Individual results will vary, and no sales or royalty outcome is guaranteed.

Whether you’re planning a Thanksgiving classroom party, looking for activities for kids at home, or need something to keep children busy while dinner is being prepared, this list has plenty of ideas to try.

My favourite? Thanksgiving word guessing game.

https://lukewarmmom.com/thanksgiving-games-and-activities-for-kids/

Hi people of r/blogs!

I work in identity and access management and started a blog about two weeks ago: adamjrg.com

It's aimed at people who look after IT at a small or mid-sized company and don't have a security team. I try to write about what to actually do first, without the vendor pitch. There's also the odd homelab project.

A few posts to give an idea:

• IAM for a small company, where I'd start

• What I learned about the SC-900 exam

• Turning an old Echo Dot into a local voice assistant

Some things I can't judge myself any more:

1. If you don't work in IT, can you follow the small company post, or does it lose you in the first few paragraphs?

2. I mix work topics with homelab projects. Does that make the blog feel unfocused, or is it fine?

3. Two posts a week is the plan. For those of you who've kept a blog going, was that too much to keep up?

If you write about security, IT or self-hosting, also let me know what you would change!

[Edit] Fixed links

Hi everyone, I'm Samantha from Langford, BC. About a month ago, I started my blog, Jammies & Justice, and this is the very first post I wrote for it:

https://jammiesandjustice.wordpress.com/2026/10/12/hi-im-samantha/

What it covers: It's really my hello to the internet. By day, I'm a mom—my daughter just started school this fall, after five years at home raising her—so I'm starting over, job hunting, working as a housekeeper in the meantime, and building my own little virtual admin business from my couch. Usually in my jammies. By night, once she's asleep, that's my time—I put on a true crime video and work on the blog, that kind of thing. The post introduces the whole blog: starting over, the true crime cases I can't stop thinking about, and couch time with my colouring books.

Why I wrote it: Because I needed a little corner of the internet that was just mine, after bedtime, once everyone else is asleep. I wanted one place to write about all three of those things, instead of keeping them separate.

Who it might help: Anyone else starting over—a parent going back to work, a career-changer, anyone building something small from their couch after the kids are in bed.

Since that first post, I've published 37 posts—true crime, starting-over updates, and couch notes—and now I have two regular clients in the books for my little business, so the blog really has become part of starting over, not just writing about it.

What I'd love feedback on: How do you introduce a blog that has a few different sides to it? And for anyone who started a blog while also building a business—what actually helped you get your first readers? I'd love to hear what worked for you.

— Samantha 💜