CodeLoom – AI analyzes, optimizes, and refactors your entire codebase

Hacker News

I built CodeLoom, an open-source tool that uses Google's Gemini models to optimize codebases. It: Analyzes your project structure Suggests overall improvements Identifies critical files for refactoring Automatically generates optimized versions of those files It works with any language or framework. I'm curious to hear HN's thoughts on AI-driven code optimization. Would you trust an AI to refactor your code? How might tools like this change our development workflows?"

Visit product View on Hacker NewsJul 26, 2024

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Actual performance

2points

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Launch Intel predictions

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

94%94% 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

53%53% 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

45%45% 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 · Strong signals: google · Missing: mobile apps, ios, personal

34%34% 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

24%24% 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

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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