IdeaWell

Project ideas from Hacker News discussions.

I verified my LinkedIn identity. Here's what I handed over

Original Article

Hacker News Discussion

📝 Discussion Summary (Click to expand)

Five dominant themes in the discussion

# Theme Representative quotes
1 Privacy & biometric data misuse “I didn’t read the terms but there’s no way I’m giving Microsoft or its minions my govt ID.” – SanjayMehta
“The data went exclusively to North American companies.” – article
“I gave in and verified. Persona was the vendor.” – luxpir
2 Forced verification as coercion “LinkedIn locked me out … wants me to verify via this same Persona company.” – SanjayMehta
“I was forced to verify to get access to a new account.” – luxpir
“I was forced to verify to access my existing account.” – kioshix
3 LinkedIn’s dual role: job‑search tool vs spam/AI‑slop “LinkedIn is a Facebook for the employed.” – andreashaerter
“LinkedIn is the ultimate intelligence test.” – talk
“LinkedIn is a sleazy platform.” – many
4 EU vs US data sovereignty & legal tension “LinkedIn is an American product. It must obey US law.” – csmpltn
“The CLOUD Act allows US law enforcement to force any US‑based company to hand over data.” – article
“LinkedIn is subject to GDPR but also US law.” – csmpltn
5 Call for alternatives / decentralisation “We need an EU alternative.” – many
“We should have zero‑knowledge proofs.” – many
“We should stop using LinkedIn.” – many

These five themes capture the core concerns—privacy erosion, coercive verification, LinkedIn’s problematic ecosystem, jurisdictional clashes, and the push for more privacy‑respecting alternatives.

🚀 Project Ideas

Decentralized Professional Network (DPNet)

Summary

  • Builds a federated, privacy‑first professional networking platform that eliminates the need for centralized identity verification.
  • Uses zero‑knowledge proofs to prove employment history and skills without exposing personal data.

Details

Key Value
Target Audience Professionals, recruiters, freelancers who want a secure, verifiable network without giving up biometric data.
Core Feature Federated graph of professional connections, ZK‑based credential verification, end‑to‑end encrypted messaging.
Tech Stack Rust + Substrate for blockchain, libp2p for peer‑to‑peer networking, zk‑SNARKs for proofs, WebAssembly for browser clients.
Difficulty High
Monetization Revenue‑ready: subscription tiers for premium analytics and recruiter tools.

Notes

  • HN users lament “forced biometric verification” and “data leakage”; DPNet offers a self‑hosted alternative.
  • The federated model invites discussion on decentralization vs. network effects.

Privacy‑First Identity Verification SDK (PFIV)

Summary

  • Provides a library that performs identity verification entirely on the user’s device, generating a zero‑knowledge proof that can be verified by any service.
  • Eliminates the need to upload passports or biometrics to third‑party servers.

Details

Key Value
Target Audience Web and mobile app developers needing KYC/AML compliance without storing PII.
Core Feature On‑device OCR, facial recognition, and ZK‑proof generation; optional integration with government e‑ID APIs.
Tech Stack Kotlin/Swift for mobile, JavaScript/TypeScript for web, Rust for cryptographic primitives, libp2p for proof verification.
Difficulty Medium
Monetization Revenue‑ready: per‑verification fee or subscription for enterprise usage.

Notes

  • Addresses pain points about “Persona” and “cloud‑based” verification services.
  • HN commenters like “I had to give my passport to Persona” will appreciate a local solution.

Verification Transparency Dashboard (VTD)

Summary

  • A web app that aggregates and visualises the data flows of popular verification services (Persona, ID.me, etc.).
  • Shows which data is sent to which subprocessors and how long it is retained.

Details

Key Value
Target Audience Privacy‑conscious users, regulators, journalists.
Core Feature Real‑time dashboards, audit logs, exportable reports, alerts for policy changes.
Tech Stack Go backend, React frontend, PostgreSQL, Grafana for visualisation.
Difficulty Medium
Monetization Hobby (open source) with optional paid analytics add‑ons.

Notes

  • HN users complain about opaque data usage; VTD gives them concrete evidence.
  • Sparks discussion on accountability and data sovereignty.

Automated Account Deletion & Data Request Service (AADRS)

Summary

  • Automates the process of requesting account deletion, data export, and privacy‑rights compliance from platforms like LinkedIn, Facebook, and others.
  • Provides a single interface to manage all privacy requests.

Details

Key Value
Target Audience Individuals and small businesses frustrated by manual deletion processes.
Core Feature Bot‑driven form submission, email tracking, legal‑document templates, status dashboard.
Tech Stack Python (Selenium/Playwright), Flask API, SQLite, email‑service integration.
Difficulty Low
Monetization Hobby (open source) with optional paid support.

Notes

  • Reflects frustration “I can’t delete my LinkedIn account without verifying” and “GDPR requests take forever”.
  • Provides practical utility for users who feel trapped by platform lock‑in.

Privacy‑First Job Board Aggregator (PFJBA)

Summary

  • Aggregates job listings from company career pages, local boards, and remote‑work portals without requiring LinkedIn or other social profiles.
  • Uses a privacy‑preserving matching algorithm that only shares minimal data with recruiters.

Details

Key Value
Target Audience Job seekers who want to avoid social‑network‑based hiring pipelines.
Core Feature Scraper‑based job feed, optional anonymous resume upload, ZK‑proof of qualifications, encrypted applicant‑recruiter communication.
Tech Stack Node.js, Puppeteer for scraping, PostgreSQL, WebRTC for encrypted messaging.
Difficulty Medium
Monetization Revenue‑ready: recruiter subscription, premium resume visibility.

Notes

  • Addresses the sentiment “LinkedIn is a black‑mail tool” and “I can get a job without LinkedIn”.
  • Encourages discussion on alternative hiring ecosystems.

Read Later