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A no-build fullstack SSR TypeScript web framework

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A no-build fullstack SSR TypeScript web framework

Hi HN! I'd love to seek your insights on a fullstack web framework that employs a different approach: no build. It's not a new concept. The folks as Preact mentioned it: https://preactjs.com/guide/v10/no-build-workflows/ However, in the Web Framework market, I've yet to find many that support both "no build" and "SSR". There's always some sorts of "client mount" and "server mount" and either has (or both have) to go through a build (bundling) process. With the build process, there comes additional maintenance efforts and cognitive load. I've enjoyed wrestling with tsconfig, webpack config, all sorts of presets and plugins countless times... When things work, they just work, but when we need sth a bit custom or unconventional, then we're almost always in for a tough ride. (or it's just me ) Not to say I'm against any existing build workflow. In fact I benefited a lot in the past from webpack, and i'm very positive about modern bundlers like Parcel 2, Turbopack, rspack, etc. I just feel it'd be fair to save some slots for the "no build" route :) To this end, I spent the last month working on a prototype of a TypeScript fullstack SSR web framework. It's compatible with Deno and Bun runtimes. I'd love to make it compatible with Node.js as well (at some point). The framework registry page ( https://jsr.io/@fullsoak/fullsoak ) summarizes the motives expressed so far. An example deployment is available at: https://fullsoak.onrender.com/app The code behind the deployment above: https://github.com/fullsoak/bun-examples PS: you may see Preact being used & mentioned everywhere but I'm positive that React is 100% supported as well (just drop-in & use). I just happened to choose Preact to experience it more for myself. I look forward to your thoughts :) and learning if this might (or might not) be a feasible idea at scale. And perhaps, which future directions you would see this (or something like it) goes. Thank you much for any insight!

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, code · 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: compatible · Missing: supports, reddit linkedin, podcasting
88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
68%68% 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
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
33%33% 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
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.

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