In the world of crypto trading, where information and reaction speed are everything, experienced players are increasingly integrating artificial intelligence into their work. One such professional, known by the pseudonym Tyler Durden, whose audience on social network X exceeds 200,000 followers, shared his working arsenal — six key prompts for neural networks that, according to him, significantly enhance trading efficiency.
Risk/Reward: The Foundation of Every Trade
The first and perhaps most important prompt forces AI to break down a trade into its components: entry point, stop-loss level, and target profit-taking levels. The neural network calculates the ratio of potential loss to potential gain. This approach is the foundation of a disciplined trader, allowing them to filter out obviously unprofitable scenarios and avoid entering positions with unjustified risk.
Macro Overview: A View Beyond the Chart
This prompt shifts focus from the technical picture of a specific asset to the global economic environment. The neural network assesses how key macroeconomic factors — interest rates, inflation, and the strength of the dollar — affect the price. This is especially valuable during periods when the market is driven less by technical signals and more by central bank decisions.
Liquidity Map: Where the Whales Hide
This prompt is aimed at finding liquidity zones — clusters of retail traders' stop orders and large institutional orders. The idea is that price often tends toward these levels, "collecting" liquidity. Understanding these zones helps not only to predict movement but also to avoid getting caught by one's own stops.
Correlation Matrix: The Illusion of Diversification
Many traders mistakenly believe their portfolio is diversified. This prompt checks how interconnected the assets in the portfolio are. If several positions move synchronously, risk is actually concentrated, not distributed. The neural network reveals hidden correlations, showing real rather than imaginary diversification.
On-Chain Signals: The Voice of the Blockchain
Using public blockchain data, this prompt analyzes wallet behavior. It looks for accumulation patterns (when large holders increase positions) or distribution patterns (when they unload assets). Such on-chain signals often precede price movements and serve as a powerful complement to technical analysis.
Portfolio Stress Test: Readiness for a Black Swan
The final prompt simulates adverse scenarios, such as a sharp market downturn. The neural network shows which positions will suffer the most. This allows for an advance assessment of the maximum possible loss and an understanding of which assets make the portfolio most vulnerable.
My comment as an analyst: Using AI for routine analysis and hypothesis testing is an evolution, not a revolution. However, it is critically important to remember that a neural network is a tool, not an oracle. All obtained data requires double-checking and personal interpretation. Technology does not eliminate responsibility for risks, but merely helps make more informed decisions.