Core – Constitutional AI achieving 70% autonomous coding

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I'm excited to share CORE v2.0.0, which just achieved A2 autonomy: 70% success rate on autonomous code generation with constitutional governance. The problem: AI agents can write code fast, but they also break architecture, skip tests, and ignore conventions. The solution: Constitutional governance. Every AI action goes through: - Constitutional audit (checks architecture, naming, placement) - Semantic validation (513 symbols in knowledge graph) - Test execution with auto-fix - Clean merge only if everything passes Real metrics: - Code generation: 0% → 70% success - Semantic placement: 45% → 100% accuracy - 513 symbols vectorized, 66 module anchors, 48 policy chunks The key innovation is making AI autonomy safe through human-authored policies that AI semantically understands. Agents operate in defined "autonomy lanes" with cryptographic governance for policy changes. Built with Python, PostgreSQL, Qdrant. MIT licensed. Next milestone: A3 (strategic refactoring across multiple files). Happy to answer questions about the constitutional governance approach!

Visit product View on Hacker NewsNov 28, 2025

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23%23% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

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