IdeaWell

Project ideas from Hacker News discussions.

I'm a developer for a major food delivery app

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

1. Skepticism About Post Authenticity

Many doubt the Reddit post is genuine, citing poor opsec, fanfic vibes, and AI generation.
"symbogra: It's the biggest clue that it's typical reddit brained fanfic."
"on_the_train: It's just another run of the mill reddit rage bait fanfic."
"jacobrussell: Pangram... came back as 'Fully AI Generated.'"

2. Plausibility of Alleged Practices

Claims ring true due to industry precedents, settlements, and anecdotes, even if the post is questioned.
"Nextgrid: Knowing the tech industry it sounds entirely plausible. I'm surprised people think this is news."
"LostMyLogin: algorithmic wage discrimination appears very well studied and verified. [links to reports/settlements]"
"avidiax: I was previously at Uber... the poster's algorithm... adds credibility."

3. Condemnation of Gig Exploitation

Outrage at tip theft, "desperation scores," fake fees, and driver abuse; calls to boycott apps.
"ramraj07: If whats written here is true... its disgusting and ill definitely not use these apps any further."
"bilekas: I would never even think to tip in the app itself. If I don't trust a company to pay the drivers a wage, why would I trust them to give them my tip!"
"whatever1: Lyft is also a scam for the drivers... How is this legal?"

🚀 Project Ideas

Delivery Transparency Scanner

Summary

  • Web/mobile app that scans receipts from food delivery apps, reverse-engineers fee breakdowns using public data and ML predictions, and flags potential scams like tip offsetting or fake priority fees.
  • Core value: Empowers customers and drivers with verifiable insights into where their money goes, rebuilding trust via data.

Details

Key Value
Target Audience Delivery app customers and drivers
Core Feature OCR receipt upload + ML fee decomposition + historical lawsuit data matching
Tech Stack React Native, Tesseract OCR, Python ML (scikit-learn), Supabase
Difficulty Medium
Monetization Revenue-ready: Freemium ($4.99/mo premium reports)

Notes

  • HN loves anti-en shittification tools; "transparency requirements" (BrenBarn), "external audit... cryptocurrency with on-chain verification" (sodafountan).
  • High utility for boycotts ("do not use the apps" i_play_stax); sparks discussions on app ethics.

Driver Desperation Detector

Summary

  • Dashboard for gig drivers to log sessions, detect algorithmic discrimination (e.g., low-pay order flooding after high acceptance), and simulate optimal strategies.
  • Core value: Helps drivers maximize earnings by identifying and evading "desperation score" traps.

Details

Key Value
Target Audience Food delivery and rideshare drivers
Core Feature Session logging API integration + anomaly detection ML + earnings simulator
Tech Stack Next.js, Node.js, TensorFlow.js for edge ML, PostgreSQL
Difficulty Medium
Monetization Revenue-ready: Subscription ($9.99/mo pro analytics)

Notes

  • Addresses "desperation score" outrage ("makes me sick" OP via Reddit); "drivers can see... prove by asking customers" (armchairhacker).
  • Practical for migrants/low-wage workers; HN debates gig exploitation ("infinite supply of suckers" lispisok).

Priority Delivery Verifier

Summary

  • Mobile tester app that runs A/B experiments on orders (priority vs standard), tracks ETAs/driver paths via GPS sharing, and proves delays are artificial.
  • Core value: Collects crowd-sourced evidence to debunk scams like delayed non-priority orders.

Details

Key Value
Target Audience Frequent delivery customers
Core Feature Order randomization + real-time GPS/ETA logging + statistical comparison dashboard
Tech Stack Flutter, Firebase, Mapbox, R for stats
Difficulty High
Monetization Hobby

Notes

  • Directly tests claims ("purposefully delayed non-priority orders" OP); "randomized trials" (armchairhacker), "client side A/B tests" (another_twist).
  • HN skeptics would validate ("without evidence... fiction" cedws); viral potential for lawsuits.

GigPay Blockchain Tracker

Summary

  • Open payment layer for gig apps using blockchain to escrow tips/fees, auto-split transparently (e.g., 100% tips to driver verifiable on-chain), portable driver profiles.
  • Core value: Forces ethical payouts with immutable audit trails, no trust in apps.

Details

Key Value
Target Audience Drivers, customers, ethical restaurants
Core Feature Wallet integration + smart contract splits + profile portability
Tech Stack Solana (low fees), React, Anchor framework
Difficulty High
Monetization Revenue-ready: 0.5% txn fee

Notes

  • Inspired by "blockchain and split payments" (adrianwaj), "on-chain verification" (sodafountan).
  • HN crypto fans engage; solves "tip theft" ("100% of tip goes to driver?" ilvez), union ideas.

DirectOrder Scout

Summary

  • Browser extension/service that detects delivery app orders, finds direct restaurant contacts/pricing, compares totals (app fees vs direct), and automates calls/emails.
  • Core value: Bypasses apps entirely, saving 20-50% while supporting locals.

Details

Key Value
Target Audience Cost-conscious customers tired of apps
Core Feature Menu scraping + price comparator + one-click direct order facilitation
Tech Stack Chrome extension ( Plasmo), Puppeteer, Twilio for calls
Difficulty Low
Monetization Revenue-ready: Affiliate commissions from direct orders

Notes

  • Tackles "buy food physically, or call... directly" (dartharva), "prioritise the app" frustration (forinti).
  • Promotes boycotts ("abstain entirely" i_play_stax); HN utility for "pretend it's 2005" (rasse).

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