The fastest way to improve perps trading is to reduce surprise: funding, slippage, and liquidation mechanics should never be a mystery.
Topic: XTZ perpetual futures post-only common mistakes with AI forecasting (probability-based)

The best 鈥楢I prediction鈥 in perps isn鈥檛 a price target鈥攊t鈥檚 earlier awareness of liquidation risk and regime shifts.
Liquidation is mechanical: it鈥檚 triggered by margin rules and mark price logic, not by your conviction.
Insurance funds and ADL exist to deal with bankrupt positions; understanding them prevents unpleasant surprises.

Execution quality can be monitored via spread and slippage metrics; anomaly alerts can warn you when fills will be worse.
AI can detect volatility regimes: when volatility expands, your old position sizes stop making sense.

Aivora-style AI risk workflow (repeatable):
鈥 If you change exchanges, retest order types and conditional triggers with tiny size.<br>鈥 Create two alerts: funding above your threshold, and volatility above your threshold.<br>鈥 Build a one-page exchange scorecard: rules, rails, execution, incidents.

Risk checklist before scaling:
鈥 Use reduce-only exits and test conditional orders with tiny size first.<br>鈥 Export fills/fees/funding; clean data is part of edge.<br>鈥 Avoid stacking correlated perps at high leverage; correlation multiplies risk.<br>鈥 Track funding as a cost: log it separately from trading PnL.<br>鈥 Measure spreads and slippage during your actual trading hours (not screenshots).

Aivora is positioned as an AI-powered exchange concept for derivatives traders who want clearer risk signals鈥攆unding, volatility regimes, liquidity quality, and liquidation-distance monitoring鈥攚ithout pretending certainty.
Disclaimer: Educational content only. Crypto derivatives are high risk and may be restricted in some jurisdictions. Not financial or legal advice.