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Firebender – A Dead Simple Coding Assistant in Android Studio

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Firebender – A Dead Simple Coding Assistant in Android Studio

I spent a couple months working on a fork of AOSP (Android operating system), creating OS baked apps, and I realized how bad the coding assistants were for Android Studio (ie. Gemini). So, I built a coding assistant plugin designed for Android Development. It's simple to use: hit `CMD+L`, and a chat window opens in a side panel on the right with context over any highlighted code or opened file. There’s options to pick the best LLMs for android development like o1, gpt-4o, and claude-3.5-sonnet. This is in its early stage, so feedback from other android developers would be super helpful - If you’re in the bay area and want free lunch/coffee, pick a time that works for you https://cal.com/team/firebender/coffee-with-firebender

Visit productView on Hacker NewsSep 16, 2024
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Actual performance

6points
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, apps, context · Missing: mac, agents, macos
89%89% 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
83%83% 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
48%48% 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: apps, month · Missing: mobile apps, ios, personal
44%44% 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
41%41% 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
22%22% 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.

Correct prediction on native model

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