🚀 Project Ideas
Generating project ideas…
Summary
- Browser extension that detects likely AI‑generated article submissions on Hacker News and adds a persistent “AI?” badge with confidence score.
- Gives readers an instant filter to hide or flag such content, reducing meta‑discussion and improving signal‑to‑noise.
Details
| Key |
Value |
| Target Audience |
HN readers and moderators who want to skip AI‑slop without engaging in comment debates |
| Core Feature |
Real‑time page‑scan using a lightweight ML model (e.g., Hugging Face DistilBERT) that returns a % AI likelihood and inserts a custom badge next to the title |
| Tech Stack |
Chrome/Firefox extension (Manifest V3), Python backend API (FastAPI), ONNX‑optimized transformer model, backend hosted on serverless functions |
| Difficulty |
Medium |
| Monetization |
Revenue-ready: Freemium with premium filter options ($4/mo) |
Notes
- Directly addresses the “just show me the prompt” and flag‑fatigue pain points raised by many commenters.
- Could be open‑sourced to gain community trust and avoid over‑blocking; allows adjustable thresholds to minimize false positives.
Summary
- Platform that lets authors voluntarily tag their HN submissions as “Human‑Written”, “AI‑Assisted”, or “AI‑Generated” and aggregates community votes to surface trusted tags.
- Provides a clean taxonomy for users to filter out AI content without relying on manual moderator decisions.
Details
| Key |
Value |
| Target Audience |
HN submitters, moderators, and avid readers seeking a reliable “human‑first” signal |
| Core Feature |
Tag submission via HN API, display badge on article fronts, community upvote/downvote to certify tags, and optional auto‑hide for low‑confidence tags |
| Tech Stack |
Full‑stack: React front‑end, Node.js/Express back‑end, PostgreSQL for tag database, HN API integration, OAuth for user verification |
| Difficulty |
Medium |
| Monetization |
Revenue-ready: Tiered pricing (Free for basic tags, $9/mo for enterprise tag analytics) |
Notes
- Mirrors the suggestion of “community‑generated tags” discussed in the thread, giving users control over what they see.
- Encourages transparency from authors and reduces the need for reactive flagging.
Summary
- Service that automatically archives the edit history, prompts, and AI‑use disclosures for any HN link, making provenance visible to readers.
- Enables authors to prove human effort and lets moderators verify compliance with the “no AI‑generated text” guideline.
Details
| Key |
Value |
| Target Audience |
HN authors, moderators, and readers interested in content provenance |
| Core Feature |
Browser bookmarklet that captures URL, extracts prompt logs from supported AI tools (e.g., Claude, ChatGPT), stores them in a public ledger, and adds a “Verified Human” badge if no AI use is recorded |
| Tech Stack |
JavaScript bookmarklet, Google Cloud Functions, Firestore for storage, simple UI for ledger viewing |
| Difficulty |
Low |
| Monetization |
Hobby |
Notes
- Solves the “how do we know it’s AI?” dilemma raised by stackghost and others.
- Light‑weight and privacy‑preserving; can be adopted as a voluntary workflow rather than a top‑down rule.
Summary
- Administrative UI that aggregates AI‑detection scores across all submissions, surfaces borderline cases, and lets moderators set dynamic thresholds for flagging.
- Reduces the manual workload and inconsistency highlighted by dang’s comments on flagging fatigue.
Details
| Key |
Value |
| Target Audience |
HN moderation team and power users who oversee submission quality |
| Core Feature |
Dashboard pulling data from HN DB, applying Pangram/Cohere detection APIs, visualizing confidence per article, and suggesting flag actions with justification templates |
| Tech Stack |
React front‑end, Django/Flask back‑end, PostgreSQL, Python detection pipelines, OAuth for moderator access |
| Difficulty |
High |
| Monetization |
Revenue-ready: Open‑source core with optional SaaS support tier ($19/mo) |
Notes
- Directly addresses the need for a “reason‑based flagging” system and better enforcement of the AI guideline.
- Could be piloted internally at YC and later opened to community contributions, aligning with HN’s open‑source ethos.
