Making LLMs Reliably Translate Natural Language Into Deterministic Logic
OwlZealousideal4779 · reddit · 2026-09-03
A Reddit post tackles a deceptively hard problem: getting an LLM to translate natural-language instructions into logic a deterministic system can safely execute. Using a trading rule example ("enter when BTC breaks the previous high only if volatility is rising, risk 1%, 2:1 reward-risk, once per candle"), the author notes generating code is easy — verifying it matches intent is hard. The proposed architecture separates interpretation from execution: the LLM converts instructions into a structured intermediate representation, validated against a strict schema and deterministic rules before compiling to executable logic. Open questions: JSON Schema vs AST vs DSL as the IR, detecting semantically wrong but syntactically valid output, and preventing silent logic drift.
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