I hype drivingly recreated my website and it was awesome

Hacker News

Hello HN, I had some christmas free time over the last two weeks (Merry Christmas btw ;-)) and used that time to completely recreate the website of my app[1]. I used all the fancy new tools. I didn't know some of them when I started. What was my goal? * Pretty website * Blazing fast * Mobile first * SSR * Webp support * Generally all the best website practices (high lighthouse score) What did I use? * Tailwindcss (https://tailwindcss.com/) * Tailwind Components (https://tailwindui.com/) * React (https://reactjs.org/) * ViteJs (https://vitejs.dev/) * Kubernetes (https://kubernetes.io/) Well what can I say. I hate creating websites, but this was an awesome experience. Never have I created a website more efficiently. Tailwindcss + Components is just the best. ViteJS is so so so much easier to setup compared to webpack and has SSR support on top of it. React has been around somewhat longer and I did a lot of projects with it, so that was a nobrainer. Special thanks to all the people who created these awesome tools. PS: If you work with lots of images, do yourself a favor and use something like https://github.com/JonasKruckenberg/imagetools. It saved me hours of dreadful work. [1] https://stockevents.app

Visit product View on Hacker NewsDec 25, 2021

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

80%80% 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.

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

65%65% 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: efficient · 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 · Missing: mobile apps, ios, personal

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: new · Missing: mac, agents, macos

32%32% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

11%11% 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.

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