# LetItBe

- **Event:** [Built with Opus 4.7: a Claude Code hackathon](https://cerebralvalley.ai/e/built-with-4-7-hackathon)
- **When:** Apr 21 at 12:00 PM – Apr 27 at 2:00 AM (EDT)
- **Where:** Online
- **Team:** [HyuckJae Lee](https://cerebralvalley.ai/u/letitbe)
- **GitHub:** https://github.com/misolove/gsuda-engine
- **Demo video:** https://youtu.be/B8CfS_e32is
- **Gallery:** https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery/55

gsuda-engine is a provenance-first self-evolving trading loop for Korean equities.

It solves a practical problem in trading agent design: generated rules should not be deployed blindly. The system logs simulated trade recommendations with full feature vectors, tracks T+5 outcomes, clusters failed trades, drafts candidate suppression rules, and then validates each rule before Risk Guardian can load it.

The project is built from what I know: 23 years operating Korean securities systems and 13 years studying Saju / Yeokhak. Saju is not treated as fortune-telling or price prediction. Instead, original Hanja-based Saju fields are preserved as domain-informed categorical features that must be tested empirically.

In the demo, one candidate rule is promoted to skills/active after passing validation, while another is quarantined because it damages too many winning trades. The broader local research warehouse covers Korean equities from 1995 to 2026, with 11M+ enriched rows and 2,700+ stocks.

Core principle: Claude drafts. Data validates. Risk Guardian deploys.

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Markdown version of https://cerebralvalley.ai/e/built-with-4-7-hackathon/hackathon/gallery/55. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt