Hyperlink.au job index powered by GPT

Hacker News

hyperlink.au is an Australian job search engine launched 2 days ago. Hyperlink.au does not crawl/index but instead let employers post job details by email which is then read by GPT, transformed and indexed. In past we had systems like Posterous where we created the content by email, however its extremely hard to code something that can consistently extract structured data from unstructured or in most cases spam emails. So I decided to try OpenAI APIs and it seems to just work. There is still a workflow where we check the data manually before it gets posted but hopefully we can get rid of that soon. Any feedback or suggestions welcome.

Visit product View on Hacker NewsMar 29, 2023

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2points

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Launch Intel predictions

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

81%81% 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.

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

78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: soon · Missing: plus, platform, intuitive

52%52% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

46%46% 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

20%20% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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