Static website that regenerates on-demand with built-in CMS

Hacker News

Some of my friends are artists and creators. Their personal websites are important for them, serving both as a showcase for new work and an archive of past creations. However, these websites often lack the dynamism of social media, which makes them somewhat boring. I've noticed that these friends of mine are reluctant to update their personal websites. They view it as a diversion from their current projects, and the tools they use can be user-unfriendly or too complex. To address this I created a simple website template that an artist can update from a desktop or phone, with as much fluidity and ease of use as possible. I also focused on low cost and zero maintenance. This is the stack I used: React, Next.js, Vercel.

Visit product View on Hacker NewsNov 15, 2023

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Launch Intel predictions

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

88%88% 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

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

53%53% predicted probability of success on TrustMRR, 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

47%47% 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: friendly · 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

16%16% 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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