Li

LinkedIn Mate – Find job opportunities hidden in the feed

Hacker News

LinkedIn Mate – Find job opportunities hidden in the feed

My wife recently re-entered the job market and we noticed a frustrating trend: many of the roles are shared as regular status updates by recruiters rather than official listings in the Jobs tab. I don't know why this became a practice, but they are very easy to miss, unlike the job listings with alerts and all kinds of search. So I built this Chrome extension over a weekend to solve that problem. It tracks specific people or companies and captures those hidden opportunities from the feed. ## Technical / Privacy approach: - Privacy-First: No data leaves the browser. Everything is stored locally. - No Monetization: It’s free. I don’t believe in charging people who are currently out of work. No ads, no data selling. - Classification: It uses simple keyword matching or optional AI classification. - AI Implementation: If you want to use the AI features, you provide your own OpenAI API key. It's stored with local encryption and I’ve optimized the prompts so it usually costs less than $0.01 per day using gpt-3.5-turbo. I'm looking for feedback on any features that would make the job hunt more manageable, in this brutal market conditions.

Visit product View on Hacker NewsJan 28, 2026

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →

Indie HackersFits the IH revenue-focused audience · Strong signals: wife · Missing: supports, reddit linkedin, podcasting

89%89% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: openai, using, open · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

49%49% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Rella63%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Discover hidden opportunities in your product.

Indie Hackers6b2b

LinkedOut59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Make your LinkedIn feed bearable again

Remote job opportunities from scouring FB48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Remote job opportunities from scouring FB

Jarbug84%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Uncover Hidden SEO Opportunities

Indie Hackerscommitment-full-time

Creworth50%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Get opportunities by showing your entourage.

Indie Hackerscommitment-full-time

Sherloq71%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Turn Linkedin signals into opportunities

Indie Hackers1$10,000/mosaas

Electronic breadboard with a hidden Arduino28%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Electronic breadboard with a hidden Arduino

Feed the Quine41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Feed the Quine

Django Filtered Feed40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Django Filtered Feed

GTFS (transit) feed normalization41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

GTFS (transit) feed normalization

Browse all products Analyze your launch