
u/cYotYot

We built a personalized AI book discovery engine to fix broken recommendation lists. Would love your feedback on our product and growth strategy!
Hey r/SaaS
My best friend and I started bookstoread.ai because we love books, but realized the internet lacks a genuinely good way to find them. Traditional discovery platforms focus entirely on bestsellers aimed at the "average reader." But the average reader doesn't exist; everyone has highly specific, nuanced needs.
When we entered this space, we focused on two core frameworks that might be useful for anyone building in AI today:
- Identify the AI leverage point: Look at an industry and find where AI changes the game completely. For books, that is discovery.
- Build a product that rides the LLM wave: Don't fight the foundational models; build on top of them. We train them to solve our specific personalization problem slightly better than a generic chat prompt can. By focusing on smart UI, custom data loops, and surfacing recent books published after the models' training cutoffs, we win. Every time the base LLMs get a native upgrade, our product instantly gets better too.
🛠️ The Tech Stack & Evals
We didn't get it right on the first try. It took iteration after iteration of diving deep into RAG and prompt engineering.
Today, our backend dynamically orchestrates across Gemini, OpenAI, and Anthropic. To make this viable, we run regular internal evaluation cycles (Evals) to constantly optimize our sweet spot between output quality, latency, and API costs.
💰 Pricing
The tool is 100% free to use.
📈 Current Growth Stage & Learnings
Our early traffic from Product Hunt and initial SEO brought in our first few hundred users. The engagement data showed us that people actually love the tool. We even started tracking downstream Amazon purchase data, proving that the intent and recommendation quality are genuinely hitting the mark.
Right now, our biggest challenge is distribution. To tackle this, we are currently building an organic content engine to scale our traffic natively.
💬 We’d love your feedback:
- The Engine: Try searching for a highly specific topic or a niche book you love. Did it actually surface a great read, or did it miss?
- Organic Growth: If you've scaled a content-driven acquisition loop for a side project before, what worked best for you?
- UX/UI: What is the number one thing you would change about the interface?
Thanks for checking it out, and we'd love to hear your thoughts on how we can improve the experience or scale our organic growth!