Market mechanics, operating notes, and rules you can inspect — written from the work of building and running the product.
Three reads, in order: understand the exchange, make the rule explicit, then test the automation on paper.
Understand contracts, prices, settlement, and the risks before automating anything.
Read step 01Turn an opinion into a testable entry, exit, sizing, and stop policy.
Read step 02Inspect the automation, run it on paper, and review its receipts before going live.
Read step 03Recurring formats for the lessons, failures, rule checks, and market evidence that do not fit a generic how-to.
What running the product teaches us about execution, risk, and reliability.
4 articles →Postmortems and checks built from failures, misleading data, and false confidence.
3 articles →One trading rule at a time, with the assumptions and failure modes exposed.
4 articles →Close readings of real market structure, data, and settlement mechanics.
4 articles →The long-form references for learning the exchange, finding a rule, and deciding what to automate.
How AI and LLMs are transforming prediction market trading — signal generation, multi-agent systems, and building AI-powered Kalshi bots.
Read the full guideWeather events, sports edges, arbitrage, market making, and more — 7 strategies with entry rules, position sizing, and worked examples.
Read the full guideA practical guide to making money on Kalshi — from your first trade to automated strategies — with disciplined risk management at every step.
Read the full guideHow Kalshi API trading works, the rules to verify, and how to build or use a bot without confusing automation with guaranteed performance.
Read the full guide51 articles · page 1 of 5
Compare Gemini Predictions and Kalshi by access, market identifiers, settlement sources, fees, APIs, sandbox support, and automation risk.
Operator guide to Polymarket Builder codes, order attribution, relayer limits, fees, verification, leaderboard visibility, and grants.
How Bot for Kalshi researches prediction markets: source hierarchy, timestamps, calculations, vendor claims, corrections, and revisions.
Use LLMs to generate prediction market signals: what they're good at, the calibration trap, and a practical pipeline with code for a tradeable signal.
Yes, you can bet on the weather on Kalshi, a CFTC-regulated exchange. How temperature, rain, and snow markets work and how to trade them.
Three ways to automate your Kalshi trading in 2026: the API, a no-code bot builder, and copy trading. How each works and how to pick the right one.
Yes, you can bet on interest rates on Kalshi, a CFTC-regulated exchange. How Fed-decision markets work, what moves them, and how to trade the FOMC.
Yes — you can bet on inflation on Kalshi, a CFTC-regulated exchange. How monthly CPI markets work, what moves the number, and how to trade the release.
Build a no-code Kalshi NFL bot: automate game-winner, totals, and player-prop markets with rule-based triggers, position caps, and stop-loss guardrails.
Build a no-code Kalshi NBA bot to automate basketball event contracts. Use supported Kalshi-price and timing rules with guardrails — no programming required.
Build a Kalshi Bitcoin bot to automate BTC price markets with defined-risk, rules-based trading: triggers, guardrails, fees, and where the edge isn't.
Research Kalshi weather markets, then automate today's NWS high/low at a supported station or a price rule, with limit orders and risk caps.
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