Modify Code by Providing Verbal Feedback

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I created Force Multiplier, which allows you to modify any text (including code) just by speaking your thoughts. Force Multiplier can take into account your verbal feedback and will use GPT-4 to modify your document before your eyes. The goal is to allow humans to review the work of machines and provide feedback until the machine arrives at our desired output. The GitHub repo is here: https://github.com/lspahija/force-multiplier A demo video is here: https://github.com/lspahija/force-multiplier/assets/44912218... You can try it out here: https://force-multiplier-production.up.railway.app/ Please let me know if you have any comments or questions!

Visit product View on Hacker NewsJun 26, 2023

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

86%86% 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: created, including · Missing: supports, reddit linkedin, podcasting

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video, way · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% 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.

Incorrect prediction on native model

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