PostFast – AI-Powered Copywriting Browser Extension

Hacker News

We built PostFast to simplify how creators and marketers generate platform‑specific copy. Instead of manually adapting the same product info for Twitter, LinkedIn, or a newsletter, you configure your product once, and PostFast uses AI to generate tailored content. Key features: - One‑time setup for your product or service - Generates copy adapted to different platforms (style, tone, length) - Includes copy scoring and A/B variant comparison - AI-powered recommendations for which version to use - All inside your browser; no external app needed It's built for indie makers, content teams, and marketers who need quick, consistent copy without jumping between tools. We focused on making it flexible and non‑opinionated—you control the inputs; the extension handles the formatting and platform nuances. We're launching soon and opening a waitlist. If you regularly write promotional copy, we'd love your feedback on: - Which platforms you post to most - What kind of scoring criteria would be useful - Whether you'd prefer a free tier with limited generations Waitlist and brief demo: [ https://postfast.today/#subscribe ] (I’m one of the developers.)

Visit product View on Hacker NewsOct 28, 2025

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

74%74% 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: new, open · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, soon · Missing: plus, intuitive, reviews

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

35%35% 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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released

10%10% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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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