InlineGPT – prompt without leaving your app

Hacker News

the problem: constantly switching apps to use AI was killing my flow. the solution: inlineGPT - the everywhere AI-copilot, trigged via one global shortcut. how it works: – write and select text in any app – hit ⌘ + Shift + 1 – AI output gets instantly pasted in works in email, figma, slack, notion - you name it. retains styles, too. Demo: https://www.veed.io/view/e19a376b-4b51-46b3-a774-6eb24d217fb... by HN standards, I know this is far from impressive. I'm a designer, not a developer. I built this (and learned some swift and xcode along the way) by just prompting Sonnet and 4o over the span of a few hours. feels great to finally launch something so thought I'd share - maybe you'll find it useful and enjoy using it. Grab it for free (...but you need you OpenAI API key): https://gumroad.com/l/inlinegpt

Visit product View on Hacker NewsJun 28, 2024

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1points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, apps, email · Missing: mac, agents, macos

90%90% 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

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

55%55% 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.

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

29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% 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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