An

Anterion – Open-source AI software engineer (SWE-agent and OpenDevin)

Hacker News

Anterion – Open-source AI software engineer (SWE-agent and OpenDevin)

Hi there! At Anterion we've been working on merging together SWE-agent and OpenDevin to enable exploring SWE-agents open-ended problem solving capabilities. Excited to share our work with the wider community and see how well SWE-bench benchmarked agents work for general programming use cases! In our experience, the guard-rail techniques used for SWE-agent do translate well to solving basic real-world tasks and could be integrated into more holistic Devin style solutions in the near future. Excited to see more collaborators join us as well!

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Actual performance

4points
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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, tasks · Missing: mac, macos, cursor
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.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
43%43% 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
14%14% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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