A bot is just a rule that runs itself
Strip away the mystique and a trading bot is a rule executed automatically: 'buy when this happens, sell when that happens,' applied without sleep, hesitation, or second-guessing. The bot brings the discipline; the quality of the rule determines the result.
That's the part most bot guides get backwards. They spend chapters on plumbing - data feeds, order execution, hosting - and a paragraph on the strategy. But the plumbing is a solved problem. The open question, always, is whether your rule actually works.
The traditional route: Python, data pipelines, and deployment
Building a bot by hand means writing Python, fetching and cleaning market data, handling partial fills, retries, and edge cases, then deploying and monitoring it - weeks of work before the first reliable run.
The shortcut is a hosted bot platform, but many still require indicator configuration and exchange-specific setup before you can test a complete strategy.
The no-code route
The modern alternative removes both the coding and the key handover:
- Describe the rule in your own words - 'hold bitcoin while it's above its 100-day average, move to cash below.'
- The AI writes the strategy as real Python - code you can read and audit, not a black box of settings.
- Backtest it on years of real candles first, so the rule earns its place before it runs.
- Run it forward on live market data, recording each simulated decision and trade as new prices arrive.
Backtest before you let anything trade
Most 'my bot lost money' stories are really 'my rule never worked' stories. A bot executes its rule faster and more consistently than you would - which means a bad rule loses money faster and more consistently too.
So the backtest isn't a preliminary; it's the point. The same rule that will drive the bot should first be run over years of history, across different market conditions, with fees included. If it can't survive the past, it has no business trading the future.
How Premiss does it
Premiss is the harness for exactly this loop: you type the rule in your own words - no code - it writes the real Python, backtests it on years of real market data, and shows you the code, the trades, and a verified result. A strategy that survives can keep running forward on live data, recording each simulated decision and trade.