An AI Review Workflow for Disciplined Crypto Trade Decisions

Summary

The document describes a proposed workflow intended to slow impulsive cryptocurrency trades. Before acting, a trader records the asset, direction, size, and rationale. The system combines that input with current position data, news sentiment, and technical indicators such as MACD, RSI, ATR, and OBV. An AI review then checks the reasoning for cognitive biases, compares it with signals and sentiment, assesses timing and risk, and returns an analysis with possible entry, exit, and risk guidance. The workflow also saves reviews to a log for later reflection.

The article explains the system architecture and gives illustrative inputs and outputs, but it does not provide controlled evidence that AI review blocks a stated share of bad trades or improves returns. Some example conclusions and suggested prices are illustrative. The author acknowledges that the tool cannot predict black swans, replace experience, or guarantee profits, and describes the framework as an early implementation that needs improvement. Its assessments depend on data quality, model judgment, and trader review.

Key ideas

• Requiring a written rationale can introduce a pause before order placement.
• The workflow combines position, news sentiment, technical indicators, and the trader’s stated rationale.
• The AI review is designed to flag weak logic, biases, timing concerns, and risk issues.
• A saved trade log can support later review of recurring decision patterns.
• The article provides a system design rather than evidence of improved trading performance.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.