Igor – AI-Powered Code Review Bot with In-Thread Discussions

Hacker News

I've often faced the challenge of waiting a long time for code reviews, which can be time-consuming. With Igor, developers get an immediate summary of changes, allowing for a quicker start to the review process. It's not just a passive tool either; you can actively ask Igor questions during the review by simply mentioning "@igor". Video demo: https://www.loom.com/share/151ca4c77a8644c28ea067fdc6294e44 Igor has been instrumental in accelerating our review cycles, and I hope others find it beneficial. We're currently opening slots for companies to join our beta for free. We'd love to have your feedback and see how Igor can further improve your code review process. Write me an email to red at codemaster.red if you're interested in joining.

Visit product View on Hacker NewsOct 20, 2023

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

80%80% 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.

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

63%63% 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: video · Missing: mobile apps, ios, personal

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

11%11% 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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