NEXUS rewrites rules after 62 sessions

NEXUS is less a trading bot than a live metacognition experiment, and the most interesting result is that its confidence appears inverted rather than calibrated.

• –The confidence gap is the real story: high-confidence calls perform worst, while lower-confidence calls do better, which suggests the model is overconfident on familiar-looking patterns.
• –The jump from 0% hit rate in the first half to 33% in the second half is meaningful, but 62 sessions is still too small to call this a durable market edge.
• –FORGE is the most compelling engineering piece here because it constrains self-modification with TypeScript validation and rollback, which makes the autonomy auditable instead of magical.
• –The weekend crypto mode and stagnation detector show the system is getting more specialized, but they also create a risk of overfitting to its own feedback loops.
• –For AI builders, the takeaway is practical: version-controlled memory, bias logging, and hard validation gates are probably more useful than letting an agent freestyle its own prompt.