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I

I made a job board exclusively for tech internships and new grad jobs

Hacker News

I made a job board exclusively for tech internships and new grad jobs

Hey HN, Over the past couple of months (in my off hours) I built Good First Job — a job board exclusively for tech internships and new grad jobs. It started as a way for me to finally tryout some of the AI tools I’ve been hearing so much about, but also attempt to build something useful. I built it with Next.js + Supabase and deployed it on Vercel. Along the way I tried out v0, GitHub Copilot, and Supabase AI assistant. It's designed based on user feedback, and my personal experience as a CS student searching for an internship and grad looking to begin my career as an SWE. Any feedback is greatly appreciated!

Visit productView on Hacker NewsJan 30, 2025
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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new · Missing: mac, agents, macos
63%63% 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 NewsMay not resonate with HN audience · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: exclusive · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, month, way · Missing: mobile apps, ios, entrepreneurs
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: started · Missing: supports, reddit linkedin, podcasting
27%27% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · 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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