Wife couldn't find a dev job so I built a tool to automate the search

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Hey everyone, My wife graduated in 2022 and she was fortunate enough to land an internship at a small startup which then offered her a permanent position. But ever since then she has been trying to find another job as a frontend dev since the current one doesn't offer any growth opportunities. She started looking in 2023 right when the job market started tanking. She's been at it for months with no success as there are little to no junior roles available and she spent most of her day refreshing linkedin to check for new opportunities. At the beginning of this year I had this idea that I could automate the job search part for her by web scraping the search results page in linkedin. This way she could focus on work/portfolio projects and check when the tool finds new job opennings. Long story short, what started as a small script evolved into a full fledged project since I realised this could help other people too. The app is an electron desktop app which uses the underlying chromium instance to download the HTML of job sites and sends it to a Supabase edge function for parsing. It doesn't search the entire site, just what jobs are shown in the URL you paste into it. As of now it supports more that 10 sources including linkedin, indeed, dice, glassdoor, flexjobs, bestjobs, we work remotely and constantly looking to add more.

Visit product View on Hacker NewsMar 10, 2024

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

95%95% 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: new, open · Missing: mac, agents, macos

75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released

66%66% 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 · Strong signals: month, way · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

19%19% 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

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