Searching protocol for "assumption drift"
Ensure AI model stability and accuracy.
Detect deviations from specifications.
Challenge assumptions, find flaws.
Detect architecture drift
Second-opinion review of plans
Monte Carlo workflows for quant trading.
Establish neutral baseline metrics for unbiased assessment.
Reproducible ML workflows
Challenge assumptions, update methodology.
Evolve knowledge via evidence-based rethink.
Evolve your knowledge system.
Supervise autonomous coding loops