8-Bit Style Pokemon – Personal Website

Hacker News

Just published my personal website v1 with some 8-bit style design that gives people nostalgia. Check it out at https://yzhx.xyz/ . You can also find the source code on my GitHub. Here are couple of takeaways from the project: - It is a Next.js app built from the template ( https://github.com/chronark/chronark.com ). I made many changes, but I appreciate the components that came with the template! - The pixel art in the background is from Brandon James Greer on YouTube ( https://youtu.be/cxjX8O6YSHI ). Please do check out their work on YouTube; they are amazing! I'm currently using it for the sake of convenience, but I plan to replace it with my own pixel art soon. - The font I used for the website is Unifont Japanese OpenType Version ( https://unifoundry.com/unifont/index.html ). It supports a wide range of glyphs from different languages, including Hanzi. If you have any questions or if there's anything you're curious about, my DMs are open on 𝕏 anytime.

Visit product View on Hacker NewsDec 10, 2023

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

71%71% predicted probability of success on Indie Hackers, 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: using, code, open · Missing: mac, agents, macos

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

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

57%57% 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

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

TrustMRRLess likely to generate early MRR · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs

47%47% 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

12%12% 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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