In the world of crypto trading, where information and decision-making speed are crucial, the use of artificial intelligence is becoming not just an advantage, but a necessity. A well-known trader under the pseudonym Tyler Durden, who has gathered over 200,000 followers on X, shared his arsenal — six specific prompts for neural networks that, according to him, help him systematically approach analysis and trade execution. Let's break down each of them from a practical value perspective.
1. Risk/Reward
This is a basic but critically important tool. The prompt forces the neural network to analyze a specific trade, calculating the optimal entry point, stop-loss level (where the position is closed with minimal losses), and the target profit-taking level. This approach allows the trader to understand in advance whether the expected return justifies the risk taken and to filter out trades with an unfavorable ratio.
2. Macro Overview
This prompt shifts the focus from the chart of a specific asset to the overall economic picture. The neural network assesses how key macro factors — interest rates, inflation, and the strength of the dollar — affect the price. This is especially useful when market movement is driven not by technical signals but by central bank decisions and the general economic sentiment.
3. Liquidity Map
The prompt is aimed at finding zones where liquidity is concentrated — clusters of stop orders from retail traders and large orders from institutional players. The idea is that price often gravitates toward levels with high volumes. Understanding these zones helps anticipate where the market might move in search of liquidity and avoid triggering one's own stop-loss.
4. Correlation Matrix
This tool analyzes how closely related the assets in a portfolio are to each other. If several positions move in sync, the portfolio only appears diversified but actually carries concentrated risk: in a market reversal, they all decline simultaneously. The neural network helps identify such hidden connections and assess real, rather than apparent, diversification.
5. On-Chain Signals
The prompt uses blockchain data — the public transaction history and wallet behavior. The neural network looks for signs of accumulation, when large holders increase their positions, or distribution, when they offload assets. Such patterns sometimes precede price movements and serve as an additional signal for technical analysis.
6. Portfolio Stress Test
This prompt tests the portfolio's resilience to adverse scenarios. The neural network models potential drawdowns — for example, a sharp market decline — and shows which positions would suffer the most. This helps assess the maximum possible loss in advance and understand which assets make the portfolio most vulnerable.
My analysis: These prompts are not a magic bullet but tools for structuring thinking. They automate routine analysis, but the final decision always rests with the trader. The key risk is blind faith in the neural network's conclusions. Always double-check the results and remember that even the smartest AI can make mistakes, especially in the volatile and irrational cryptocurrency market.