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Can we have Flutter-like portability without the bloated web binaries?

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Can we have Flutter-like portability without the bloated web binaries?

I’ve been spending the last few months building Coi, a type-safe language that compiles to WebAssembly. The initial goal was just a fast, reactive web language, but as I refine the core, I’ve started mapping out how to take this multi-platform, mobile, desktop, and server, without falling into the traps that other frameworks have. The plan is to use C++ as the intermediate layer. For desktop and mobile, I want to use Skia combined with a layout library to translate HTML/CSS sizing and transformations into something Skia can draw. This ensures the UI stays pixel-perfect across platforms. However, the "Flutter approach" to the web has always bothered me. Shipping a 2MB+ Skia binary just to render a basic landing page feels redundant when the browser already has a world-class rendering engine. It results in massive bundles and a canvas-only UI that breaks basic browser expectations like SEO, text selection, and accessibility. With Coi, I want to split the strategy: on the web, it stays lean by using the browser’s native HTML/CSS and JS glue. On native platforms, it uses the C++/Skia stack. You get the same codebase and the same visual output, but the web build doesn't suffer from "canvas bloat". Right now, I’m still focused on the web target and refining the core language specs, but the server target is next on the roadmap. I'm curious if this "hybrid rendering" approach, native elements for web, Skia for desktop/mobile, is something others have found success with, or if I'm underestimating the difficulty of keeping the layout engines perfectly synced. I'd love some feedback on the language design or the architectural plan. https://github.com/coi

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Product HuntOn track for Day 1 leaderboard · Strong signals: visual, using, code · Missing: mac, agents, macos
84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews
53%53% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
53%53% 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: month, way · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
15%15% 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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