What running the product teaches us about execution, risk, and reliability.
What running the product teaches us about execution, risk, and reliability. 4 articles
How to run a Kalshi trading bot 24/7 in production: process management, secrets, reconnect logic, idempotency, and the failure modes that cost money.
Risk management keeps an automated Kalshi bot alive. The four controls every bot needs: position sizing, stops, daily loss caps, and exposure limits.
Legacy Kalshi order responses can omit a usable fill price. Reconcile current count_fp and yes_price_dollars fill records to keep bot P&L accurate.
Kalshi does not publish an automated-volume share. Here is what the official API proves, what public data cannot identify, and what automation changes.
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