Field reports from our editors trading AI + crypto with real capital. Monthly tracking, tool reviews, and the failure postmortems we publish on purpose.
An AI is good at turning your risk tolerance into a concrete parameter table, and bad at pressing the button — it has no live book, no view of your whole position, and no stake in the outcome. Order-type mechanics, a three-part prompt skeleton, and the three mistakes that show up most.
If AI only reads your account, it only needs a read-only key: the three permission tiers, what a leak of each actually costs you, IP whitelists, and the withdrawal-permission trap.
Seven real losing-money scenarios: asking AI to predict prices, pick coins, size leverage. Each one comes with a case where we or our readers actually lost money, and why you shouldn't use AI that way.
Five red flags that catch a fabricating AI early: oddly precise unsourced numbers, citation links that don't open, contract addresses that aren't on-chain, absolute tone, answers that mirror your assumptions too cleanly.
Three losing trades and a teardown of KOL sentiment noise. We piped Grok-flagged X signals into our trading account for 30 days. The account drew down 12%. This is where it broke, and where the signal-to-noise line actually sits.
60 days, 100 consecutive Auto-Invest orders, full data tables and a debrief. How DCA actually performs in chop vs. a one-way trend — not the marketing version.
Same signals, two accounts: one executed by AI, one by a human. 30 days of paired data, the charts, and our read on why the gap looks the way it does.
Three real rug pulls dissected: which red flags the AI caught early, and the one project that slipped past us — plus why.
200 runs of the same prompt, the full output distribution, the bull/bear hallucinations, and the verification protocol. How far you can actually trust an AI as a TA assistant.
Subscribe for updates or pitch a topic: [email protected]