AI and automated crypto trading
Guides, strategies and research
Onchain.
Off emotion.
Clear guides to trading bots, AI systems and automated crypto strategies—what they do, where they fail and how to evaluate their claims.
The articles start with the mechanics, then examine costs, controls, performance evidence and risk.
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How automated trading actually works.
Start with the basic terms and how each system works, then move into strategy mechanics, costs, common failures and the evidence behind performance claims.
Trading bots
How signals, exchange APIs, custody, order execution and fees fit together, plus what happens when data or exchange connections fail.
AI for trading
A category guide to analysis systems, signal services, execution bots, assistants, autonomous agents and managed products.
Automated systems
How an automated trading system turns market data into orders, with sizing, policy checks, monitoring and recovery along the way.
DeFAI
A practical guide to AI-assisted and autonomous DeFi workflows, from interfaces and agents to wallet permissions and policy controls.
AI trading agents
How AI trading agents differ from assistants and bots, and what must constrain an agent before it can act on capital.
Onchain asset management
How an onchain managed product handles deposits, allocation, policy, valuation, withdrawals and evidence across smart contracts and trading venues.
AI trading apps
How to compare AI trading apps by following the path from a model suggestion to an order, including custody, permissions and failure handling.
Social trading
How social trading, leader-following and copy mechanics work, including execution lag and platform risk.
Crypto algo trading
How spot and perpetual algorithms move from an idea to live orders—and where backtests tend to overstate results.
Trend following
The mechanics of systematic trend following, from regime persistence and breakout logic to whipsaw risk and execution costs.
AI scalping
How spreads, latency, turnover and fees affect AI scalping and crypto scalping bots—and why speed alone does not create an edge.
Crypto copy trading
What happens between a leader trade and a follower fill, including lag, sizing differences, slippage and platform risk.
Futures trading bots
How futures trading bots handle leverage, perpetual funding, margin and liquidation, and which controls matter before live use.
Arbitrage bots
How price, triangular, basis and funding-rate arbitrage work after fees, slippage, latency and missed or partial fills.
Funding arbitrage
How funding-rate arbitrage and crypto carry trades work, including hedge drift, changing basis and liquidation risk.
Four useful rules
04
- 01
A backtest shows how rules behaved on selected historical data. It is not a live return.
- 02
Automation removes keystrokes. It does not remove market risk.
- 03
A cryptographic proof can verify a defined claim—not profitability itself.
- 04
The real edge is what remains after fees, slippage and failed execution.
How we handle claims
If we cannot show what a claim covers, when it was measured and what it leaves out, we do not treat it as fact.