Market mechanics, operating notes, and rules you can inspect — written from the work of building and running the product.
Kalshi lists a football slate every week of the season. These two reads cover what a bot can and cannot do on those markets.
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.
5 articles →Postmortems and checks built from failures, misleading data, and false confidence.
4 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.
5 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 guideHow traders look for an edge on Kalshi, account for fees, set bankroll rules, and avoid five expensive mistakes. Beginner to advanced.
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 guide58 articles · page 1 of 5
How Kalshi's 15-minute Bitcoin markets work: target price, CF Benchmarks settlement, fees and liquidity, plus what 6,298 settled windows say about strategy.
What prediction market bots do, which trade Kalshi or Polymarket, what they cost, and how to vet one before you connect a key. Publisher-disclosed.
Find archived Kalshi markets, trades, fills and orders. Use moving cutoffs, pagination and a coverage manifest to identify gaps in your research export.
Trace a Kalshi order using its status, remaining quantity, queue position and fills. Includes a partial-fill example and a practical support checklist.
Yes — Kalshi is a CFTC-regulated US exchange. How prediction markets work, how Kalshi makes money, how it differs from a sportsbook, and the real risks.
Ten common Kalshi trading mistakes, in postmortem form: what traders expected, what happened, the root cause, and the guard that fixes it.
How a CFTC-regulated event exchange differs from a licensed sportsbook: pricing, account limits, early exit, state access, fees, and bot automation.
What a Kalshi sports bot automates today: live game state, injury headlines, price and timing rules, limit orders, paper mode — plus three starter rules.
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.
Join the free live build on October 27 at 6:00 PM Pacific. Bring a market and a rule, or just watch. We’ll build a draft, review the workflow, demonstrate paper mode, and answer your questions.
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Bot for Kalshi