I

I made a highly opinionated web builder

Hacker News

I made a highly opinionated web builder

Hey folks, This is my longest and most complex side-project, which took me approximately ~500 hours of work. - Background I like front-end programming but don't like the process of web design. Implementing design in Figma and then reworking it in HTML feels redundant. I want to skip Figma if possible. A solution to streamline that process would be a web builder, I thought. But a web builder like Webflow feels so much more complicated, they GUI-fied every CSS rule. Everything become sliders and buttons just to set a few line of CSS. Framer is a better alternative than Webflow, but still, sometimes I can't figure out how to do things that are usually so trivial in CSS. Not to mention that it also doesn't support exporting code. - Solution I just want a web builder that's basically just text editor but with a few of DX improvements. I think it would be a good idea to couple something like this with a utility-first CSS framework like TailwindCSS. Sure, some people hate Tailwind, but I've been sold to the idea of utility-first CSS since before Tailwind era (using Tachyons). It really improves my dev velocity and I think it can be improved further if there's a better tool that interface with it. That's why I made Rakit Studio. You should really check that out. It's free, basically like JSFiddle but crafted specifically for creating web pages with TailwindCSS. Feedback is really appreciated. Cheers and have a happy day! :D

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
85%85% 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 · Missing: mac, agents, macos
82%82% 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 · Missing: https docs, excited, just released
66%66% 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: interface, builder · Missing: plus, platform, intuitive
63%63% 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
44%44% 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.

Incorrect prediction on native model

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