Pe

Pen – A writing tool where conversation is the editor

Hacker News

Pen – A writing tool where conversation is the editor

Hi HN, I’m the maker of Pen. In Pen, you don’t edit the text directly. You write and revise through AI conversations inside the document. Each conversation and the edits it produces stay attached to the relevant text, so you can return to a passage to see how it took shape. Start with an idea and tell Pen what you want to write. As the text takes shape, click a sentence or select a few words, then tell Pen what you’d like to change. Your selection shows Pen which passage you mean; it doesn't limit the edit. Your request determines what changes—from a single word to the whole piece. I built Pen to change how writing gets done in the age of AI. What we stand for: 1. No editor. AI writes in your document, not in a chat. 2. Never let AI do your thinking. 3. Every factual claim must be backed by a verifiable source. 4. Collaborative. Readers can suggest changes. You decide what to accept. 5. Free for individuals. You can try Pen at https://pen.xyz without signing up. I’d love to hear how it feels in practice. How do you like this way of writing and revising versus the usual chat window?

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Actual performance

4points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: single · Missing: mac, agents, macos
71%71% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
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
30%30% 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
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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