I built a self-evolving AI that rewrites its own rules after every session. After 62 sessions, it's most accurate when it thinks it's wrong.

Reddit r/artificial / 3/21/2026

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Key Points

  • NEXUS is an open-source market analysis AI that runs 3 automated sessions per day, analyzes 45 financial instruments, and outputs trade setups with entry, stop, and target levels.
  • It incorporates a self-reflection loop to identify cognitive biases and rewrites its own rules and system prompt, with every change version-controlled and publicly available in Git.
  • The system uses FORGE to patch TypeScript files, validate with the compiler, and revert on failure, with protections that prevent touching security-critical files.
  • On weekends it switches to crypto-only using live Binance data, and its rule set expanded from 10 to 31 self-generated rules, including weekend-specific crypto rules.
  • After 62 sessions, findings show that high confidence predictions have low hit rates, uncertain predictions perform better, pure bias calls underperform, and overall hit rate rose from 0% to 33% in the latter sessions.

NEXUS is an open-source market analysis AI that runs 3 automated sessions per day.
It analyzes 45 financial instruments, generates trade setups with entry/stop/target levels, then reflects on its own reasoning, identifies its cognitive biases, and rewrites its own rules and system prompt.
On weekends it switches to crypto-only using live Binance data.

The interesting part isn't the trading — it's watching an AI develop self-awareness about its own limitations.

What 62 sessions of self-evolution revealed:

- When NEXUS says it's 70%+ confident, its setups only hit 14% of the time

- When it's uncertain (30-50% confidence), it actually hits 40%

- Pure bullish/bearish bias calls have a 0% hit rate — "mixed" bias produces 44%

- Overall hit rate improved from 0% (first 31 sessions) to 33% (last 31 sessions)

- It developed 31 rules from an initial set of 10, including self-generated weekend-specific crypto rules after the stagnation detector forced it to stop complaining and start acting

Every rule change, every reflection, every cognitive bias it catches in itself — it's all committed to git. The entire mind is version-controlled and public.

It even rewrites its own source code through FORGE — a code evolution engine that patches TypeScript files, validates with the compiler, and reverts on failure. Protected files (security, forge itself) can never be touched.

Live dashboard: https://the-r4v3n.github.io/Nexus/ — includes analytics showing hit rate, confidence calibration, bias accuracy, and a countdown to the next session.

GitHub: https://github.com/The-R4V3N/Nexus
Consider giving Nexus a star so others can find and follow its evolution too.

Built with TypeScript and Claude Sonnet. The self-reflection loop is fully autonomous, but I actively develop the infrastructure — security, validation gates, new data sources, the analytics dashboard. NEXUS evolves its own rules and analysis approach; I build the guardrails and capabilities it evolves within. It started with 10 rules and a blank prompt. The 31 rules it has now, it wrote itself.

submitted by /u/R4V3N-2010
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I built a self-evolving AI that rewrites its own rules after every session. After 62 sessions, it's most accurate when it thinks it's wrong. | AI Navigate