OpenAI-Based Writing Assistant

Hacker News

Hello HN, I'm excited to share PageThinker, a writing assistant using the OpenAI API. You can get started for free without signing in: just enter a text you would like to edit and click the suggestions button in the top right. Unlike existing grammar checkers like Grammarly, PageThinker is optimized not just to improve grammar, but to improve content and rhetoric in a context-specific way. This is one of the strengths LLMs have over traditional ML models, having been trained on so much data in so many different contexts and even different languages. In addition to the default settings, there is some ability to use custom settings and natural language prompts to improve suggestions. Lots of new features are in the works. I hope you find this useful!

Visit product View on Hacker NewsOct 11, 2023

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

92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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Hacker NewsStrong engagement from HN community · Strong signals: excited, exist, existing · Missing: https docs, just released, lua

64%64% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

51%51% 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

11%11% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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