attainable – The fastest and easiest way to design and deploy APIs

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This began as a passion project and an opportunity to learn new tech. I've always experienced frustration developing APIs, especially the RESTful CRUD style of data APIs. It always felt like I was repeating the same patterns over and over again, and that was tedium I didn't want. A little over a year ago, I wanted to learn more about Go, Firecracker microVM, and Svelte and thought "Could I build an API framework that was just a simple description of resources? What would that look like?" That lead me to https://firecracker-microvm.github.io/ , which landed me on https://fly.io , then https://rqlite.io , and the further I got into it, the more I really liked what I had. It's been over a year of learning and trying out all forms of tooling, CLIs, LSPs, and finally I landed on this. So I decided to try my hand at making this a product. I'd really enjoy feedback about it and whether it's something folks would use. Here's hoping others feel the way I do about APIs and the developer experience building them!

Visit product View on Hacker NewsDec 28, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, apis · Missing: mac, agents, macos

93%93% 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 · Missing: supports, reddit linkedin, podcasting

87%87% predicted probability of success on Indie Hackers, 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

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: way · Missing: mobile apps, ios, personal

49%49% 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

29%29% 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.

Correct prediction on native model

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