LevelCodeAI

TrustMRR

LevelCode is an AI-native code editor for macOS — open source (MIT, built on Code-OSS). Its agent plans, edits across files, runs commands, and verifies its own work behind approval gates: every edit lands as a reviewable Keep/Undo change, and every turn is a checkpoint you can rewind. Bring your own key (Claude, OpenAI, Ollama, any OpenAI-compatible) and run free and direct — or switch on the metered LevelCode Cloud gateway and pay each model's real cost, never a markup.

Visit product View on TrustMRRJul 1, 2026Artificial Intelligence Software B2C

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Actual performance

3customers

$109MRR/mo

Did not reach leaderboard

Launch Intel predictions

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

99%99% 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: compatible · Missing: supports, reddit linkedin, podcasting

63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

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

30%30% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

20%20% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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