I made a macOS app to support Anthropic Claude

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I'm a hardcore LLM user who's been switching from OpenAI to Anthropic because I feel Claude 3.5 Sonnet's responses are just better. When Anthropic released their system prompt for Claude, I decided to create my own macOS app. Because I found myself open too many browser tabs, it is just annoying that I need to search through tons of tabs to locate the Claude tab whenever I needed it. I added some other features like customized prompt shortcuts and the capability to get responses from OpenAI and Gemini for comparison. Sometimes I just want to know what they can give me. My own version runs on Supabase, but to keep this free for everyone, I made this version save everything locally on your mac, I give 10 message everyday to people for free (hope you can give me some feedback), after that you may need your own API key, which is also saved locally on your machine. Hope you enjoy it and please use the feedback button in the app to share your thoughts with me. Thank you!

Visit product View on Hacker NewsOct 14, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, claude · Missing: agents, agent, cursor

98%98% 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 · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

58%58% predicted probability of success on Indie Hackers, 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

32%32% 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 · Missing: mobile apps, ios, personal

30%30% 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

23%23% 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

16%16% 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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