Convert keywords into clickable links

Hacker News

I built a tool called LazyLink to solve a problem I kept running into. You know when you’re writing blog posts, affiliate content, or even updating a website, and you have to keep adding links to certain keywords over and over again? It’s such a time-drain. So, I made LazyLink — a simple tool that automatically converts your defined keywords into clickable links. You just tell it what words to link (like “Google” to google.com) and then paste in your content. It spits out the linked version in Rich Text, Markdown, or HTML, ready to go! No more manual linking. Check it out if this sounds like something you could use! Would love your thoughts or suggestions for improvement.

Visit product View on Hacker NewsOct 21, 2024

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Actual performance

6points

Did not reach leaderboard

Launch Intel predictions

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

62%62% predicted probability of success on AppSumo, 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: google · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

59%59% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

45%45% 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: google · Missing: mobile apps, ios, personal

33%33% 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

14%14% 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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