Section
AI / ML
Stack
LLM · Chain-of-Thought · Reasoning · Python
Category
LLM Systems · Chain-of-Thought
Status
Core pipeline working, confidence calibration in experimentation
01 — Challenge
The core engineering challenge
Base LLMs conflate reasoning and generation — the same forward pass produces both the thinking and the answer, making it hard to evaluate or improve reasoning quality independently.
03 — Decisions
Engineering decisions and what they cost
01Separate the reasoning trace from the final answer so each can be evaluated individually.
02Force structured output at each stage using constrained decoding rather than post-hoc parsing.
03Score confidence explicitly so the pipeline can escalate uncertain decisions to a human.
04 — Stack
LLMChain-of-ThoughtReasoningPythonStructured Output