I made "Who's Hiring?" searchable using GPT and Metabase

Hacker News

I vibe-coded a small project that turns the “Ask HN: Who is hiring?” thread into searchable job data using OpenAI, PostgreSQL, and Metabase. It pulls the thread using the Hacker News API, uses GPT to extract fields like company, role, location, salary, and contact, stores everything in PostgreSQL, and spins up Metabase so you can explore and search the results. Right now it runs locally, but would anyone be interested if I built this out a bit more and made a public dashboard?

Visit product View on Hacker NewsMay 21, 2025

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

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

51%51% 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

39%39% predicted probability of success on AppSumo, 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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