ReadAgain
Visit the live site →- Status
- Live
- Platform
- Web (Next.js/Supabase)
- Type
- Lean Product
- Focus
- AI-generated book recommendations grounded in the reader's own emotional memory
There's a large set of people today who've completely checked out of reading. Whether they never quite connected to it, find themselves increasingly pulled away by their phones, or just haven't found that one book to pull them back in, it's become evident that our passion for reading has been fading. But almost everyone, at some point, has had a moment where a book truly connected with them. Other tools in this space have optimized for genre and popularity, but not what actually makes a reader feel drawn to a book, the why behind the connection.
ReadAgain starts the journey by asking readers to return to a book (or a few) they truly remember connecting with, and to recall why, what was it that resonated with them. From that input, it builds a first Reader DNA profile and starting set of five recommendations, each explained by tracing it back to the reader's own memories. From there, the reader begins their journey back into reading: discovering new books aligned with what they actually connect with, and learning more about themselves as a reader as their DNA keeps evolving.
- Decision 1
Guided, emotionally specific onboarding over multiple-choice.
Shallow, impersonal onboarding leads to poor recommendations and personalized experiences. ReadAgain's onboarding guides readers through reflective questions instead of checkbox categories, improving the overall quality of the product.
- Decision 2
Explain through memory, not metadata.
Recommendations are framed around the reader's own past or current reading experiences, not genre tags or "similar users."
- Decision 3
An evolving profile, not a one-time quiz.
The Reader DNA is not a fixed, stagnant output at onboarding. It develops as the reader engages with more recommendations, so the product deepens its understanding of them over time, continuously improving the reader's experience.
Live at readagain.app, gathering feedback as readers are building their Reader DNA profiles and receiving recommendations grounded in their own memories of the books that mattered to them.
