When LLMs Outsmart Their Own Rules: Resolving Configuration Drift in AI Trading

Description and use

<h1> When LLMs Outsmart Their Own Rules: Resolving Configuration Drift in AI Trading </h1> <p>It’s 3:00 AM, and your automated crypto trading agent is scanning the markets. It identifies a setup, processes the on-chain data, and prepares to execute a swing trade. The dynamic prompt explicitly tells the Large Language Model (LLM) to proceed because the asset's crypto score is ≥ 30. The LLM generates a "PROCEED" ruling. The trade executes. </p> <p>But there’s a catch: the underlying execution engine actually enforces a hard-coded safety threshold of 65 for this specific strategy. The prompt was

Problem

<h1> When LLMs Outsmart Their Own Rules: Resolving Configuration Drift in AI Trading </h1> <p>It’s 3:00 AM, and your automated crypto trading agent is scanning the markets. It identifies a setup, processes the on-chain data, and prepares to execute a swing trade. The dynamic prompt explicitly tells the Large Language Model (LLM) to proceed because the asset's crypto score is ≥ 30. The LLM generates a "PROCEED" ruling. The trade executes. </p> <p>But there’s a catch: the underlying execution engine actually enforces a hard-coded safety threshold of 65 for this specific strategy. The prompt was

Outcome

<h1> When LLMs Outsmart Their Own Rules: Resolving Configuration Drift in AI Trading </h1> <p>It’s 3:00 AM, and your automated crypto trading agent is scanning the markets. It identifies a setup, processes the on-chain data, and prepares to execute a swing trade. The dynamic prompt explicitly tells the Large Language Model (LLM) to proceed because the asset's crypto score is ≥ 30. The LLM generates a "PROCEED" ruling. The trade executes. </p> <p>But there’s a catch: the underlying execution engine actually enforces a hard-coded safety threshold of 65 for this specific strategy. The prompt was

Evidence

When LLMs Outsmart Their Own Rules: Resolving Configuration Drift in AI Trading

Source