IdeaWell

Project ideas from Hacker News discussions.

Ask HN: What did you read in 2025?

Hacker News Discussion

📝 Discussion Summary (Click to expand)

1. Science Fiction Series Dominate Recommendations

Users heavily praised epic sci-fi series for their world-building, immersion, and reread value.
"Hyperion Cantos... 'wait I didn't know it was allowed to come up with a story this good'." - mckirk
"Stormlight archive by brandon sanderson. great escapism!" - ThouYS
"Dungeon Crawler Carl - I laughed, I cried, perfect match for my sense of humor." - bwb

2. Rediscovery of Classics and Literary Fiction

Many shared joy in rereading or first-time reads of timeless novels, noting their relevance and emotional depth.
"The Count of Monte Cristo... one of the greatest stories ever told." - kretaceous
"Grapes of Wrath - It's definitely the most heart-wrenching book I've ever read." - aabiji
"Crime and Punishment... the novel I enjoyed the most in my life." - amunozo

3. Non-Fiction on Tech, History, and Self-Improvement

Tech pros endorsed practical books on systems, business, and history, often tying to career insights.
"Designing Data-Intensive Applications by Martin Kleppman" - arvid-lind (multiple echoes)
"Apple in China" was pretty good! - neuralkoi
"Meditations... My biggest takeaways were the inevitability of death and generally letting go of our sense of control." - bencornia

🚀 Project Ideas

AudioLibrarian: Dynamic Dynamic Range Normalizer

Summary

  • A specialized audio processing tool for classical and spoken-word enthusiasts who transition between environments.
  • It solves the "whisper-to-scream" volume gap in classical music and high-fidelity narrations by allowing users to normalize audio peaks while preserving clarity.

Details

Key Value
Target Audience Audiophiles, audiobook listeners, and classical music fans.
Core Feature Smart normalization of "dynamics" (soft/loud transitions) for mobile/outdoor listening.
Tech Stack Python, FFmpeg, WebAudio API.
Difficulty Medium
Monetization Revenue-ready: One-time purchase for desktop app or monthly mobile subscription.

Notes

  • "I turn it up to hear the soft notes... only to have to go back inside to turn it down when the louder sections begin. The only thing that comes to mind is doing some sort of normalization." (sillyfluke)
  • Solves a specific pain point for listeners of composers like Chopin where the volume range is too wide for variable-noise environments (balconies, commuting).

BookFilter Pro: HN-Curated Discovery Engine

Summary

  • A book discovery platform that bypasses algorithmic "filler" by ranking titles based on sentiment and discussion density from technical communities like Hacker News.
  • It solves the frustration of "AI-slop" and "garbage" reviews on traditional platforms like Goodreads.

Details

Key Value
Target Audience Readers seeking high-signal, non-fiction and speculative fiction recommendations.
Core Feature Scraped community sentiment analysis and technical-accuracy ratings.
Tech Stack GPT-4o-mini (for sentiment), Postgres, React.
Difficulty Low
Monetization Revenue-ready: Affiliate links (Amazon/Bookshop) or Premium "Curated Lists."

Notes

  • "Lovely app which scrapped all good reads reviews and let you simply filter through that because for some reason, these pages are garbage." (hsuduebc2)
  • Addresses the recurrent complaint about "AI generated slop" (bronco21016) in modern tech and AI book releases.

MultiPass: The Serialized Fiction Adapter

Summary

  • A publishing service and e-reader plugin that converts long, "unreadable" classics into a daily or weekly serialized format.
  • It replicates the original 19th-century reading experience (e.g., Dumas, Dickens), reducing the "slog" of long novels by pacing the reader.

Details

Key Value
Target Audience Readers struggling to finish "big" books like The Count of Monte Cristo or Les Misérables.
Core Feature Splits epics into original publication "installments" with scheduled delivery.
Tech Stack Ruby on Rails, Calibre API, SendGrid/SES.
Difficulty Medium
Monetization Revenue-ready: "Sponsorship" model or pay-per-book serialization schedule.

Notes

  • "Try to read it over a course of some years. Read a little, come back to it... authors got paid by installment, so that explains the length." (motoboi)
  • Solves the problem where readers find classics "repetitive and very hard to follow" (dabiged) because they are designed for binge-reading, though they were written for serialization.

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