Learn faster with AI-tailored books
Here's how I validated, built, and launched TailoredRead
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TailoredRead is live on Product Hunt! 🎉
Today, I'm excited to share that my latest product, TailoredRead, is launching on Product Hunt! If you have a second, please check it out and show your support:
What is TailoredRead?
TailoredRead helps you learn any subject faster with an AI-tailored book.
You specify your subject of interest, background, and goals, and get a custom book crafted just for you within 10 minutes:
TailoredRead can create tailored books about almost any imaginable subject.
For example, instead of reading ten generic books about entrepreneurship, you can create one highly specific book based on your background, challenges, and goals.
This can make learning easier, save you days of reading, and help you reach your goals faster.
An idea long time in the making
I’ve always been very passionate about knowledge. In the past decade, along with some brilliant people, I’ve created products that make knowledge more accessible, such as Wikiwand, BookAuthority, and The Master List.
As an avid reader, one thing that I always find frustrating about nonfiction books is the signal-to-noise ratio: You can spend hours reading a 300-page book, only to find that less than half of the content is actually relevant to your interests, goals, and skill level.
You often need to explore many books, review their outline and samples, determine which books match your interests, goals, and skills, and you still end up with books that are one-size-fits-all and aren’t personalized for you.
Earlier this year, I wondered: what if we could flip this model on its head?
Instead of adapting your learning journey to what existing books have to offer, what if books could adapt to your learning journey?
How I validated the idea
Before writing a single line of code, I wanted to validate this idea. I ran a simple Google Forms survey letting people apply for an AI custom-tailored book.
I promoted the survey on BookAuthority, and within weeks, I gathered hundreds of responses from people who wanted to create a book.
This accomplished several things:
I found that people are open to creating and reading AI-crafted books, therefore validating my basic hypothesis.
From the comment, I learned that many people are curious about this concept and that it solves their need to learn faster and in a more focused manner.
I learned who my target audience is.
I built up a waiting list of 400+ people who want an AI-tailored book
I learned a lot: what kind of books people want to create, what goals they want to accomplish, what’s important to them in a tailored book, and more.
This was invaluable and very revealing, as some of the answers really surprised me:
I didn’t think producing a PDF version was part of the MVP, but it turns out PDF is how most people wanted to consume their books:
Also, I initially thought the product would target experts who want specialized advice, but it turns out many people are interested in reading a book tailored for them, regardless of their level of expertise:
Insights from customer interviews
It has become clear that there was a demand for the product, and now I had a lot of data in my hands.
I started by analyzing the survey data (443 participants x 12 questions) with help from ChatGPT and Claude and revising my initial hypothesis of the product. No hypothesis survives contact with the customer.
While the survey provided good quantitative and qualitative data, I figured I still needed to talk to customers to better understand their needs and expectations of the product
I emailed the waiting list, offering free tailored ebooks when the product launches in return for a quick 30-minute Zoom call:
Over the next couple of weeks, I interviewed a dozen customers and learned more about their goals, reading habits, and needs. I learned why they decided to sign up and what their expectations of the product are. These interviews also fortified my conviction that there’s a real demand for that product.
Building TailoredRead
Equipped with all that knowledge, I had a pretty good idea of the product that needed to be built.
I usually work on an MVP for a few weeks and launch it.
However, this time, it was clear that the product might take a while to build, so I decided to break down the MVP into several, incremental MVPs, each one derisking a specific aspect of the product. I then made 3 soft launches, spending about a week on each one:
Soft launch of book-generation engine - validating the technical capability to create well-written, cohesive, full-length books with state-of-the-art AI.
Soft launch of sign-up and book creation flow - validating the conversion from website visitors to engage users who end up creating a book.
Soft launch of payments - validating the pricing strategy and users’ willingness to pay for AI-created books.
willingness to pay
After these milestones, I transitioned into continuous-delivery mode, where every day, I make incremental improvements to the product.
Learning from real customers
Over the past couple of months, I’ve been learning from our early customers, and iterating on the product and marketing. Here are a few things that I’ve learned:
Trust building: many potential customers wanted to see what a book might look like before purchasing, so I set up an Explore Page where you can see samples of 100+ books created by real users, with their permission.
Signup flow: while the initial sign-up and book creation flow were fairly good, we still had quite a few barriers and drop-off points in this process of creating a book. Some were already fixed, and some are still unresolved.
Commercial licensing: while all books were sold with a license that allows personal use, several educators and authors reached out regarding commercial licensing that would allow them to distribute the books they create, so I recently introduced additional licensing options.
Mobile responsiveness: building a Kindle-alike paginated online reader proved to be difficult. Unfortunately, my initial implementation was not great, and books were not readable on certain resolutions. I had to rebuild a large portion of the online reader so that the display is adaptable and readable at various resolutions.
PDF download was unreliable: in an MVP fashion, I started by having users download their PDFs with the browser’s print dialog. Many users had problems with this mechanism, and it yielded a lot of support tickets. I ended up creating a job to render a book as a PDF on the backend, which wasn’t as big a deal as I thought (thank you, Cursor + Claude 3.5). As a bonus, users can now download PDFs in both tablet and phone resolutions.
The public launch
I’ve been iterating on TailoredRead and improving it for the past few months, and recently, I finally felt like the product is mature enough for a public launch.
Today, I’m very excited to launch it publicly! 🎉
TailoredRead is live on Product Hunt today, and I would really appreciate your support:
Got any thoughts or questions about the product or the process? I’ll be on Product Hunt all day to answer your questions!
Talk soon,
- Lior
P.S. If you decide to give TailoredRead a try, use the code LAUNCH50 at checkout to get your tailored book for 50% off.
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