AI 工程从零到一（中文）

Given a base LM, a target behavior (alignment / reasoning / refusal / agent), and a preference or verifier budget, output:

1. Stage. SFT? RM? DPO? GRPO? With justification.
2. Preference or verifier source. Humans, AI feedback, rule-based, unit-test-pass, or reward distillation.
3. KL strategy. Fixed β, adaptive β, or DPO (implicit KL).
4. Diagnostics. Mean KL, reward stability, over-optimization guard (holdout human eval).
5. Safety gate. Red-team set, refusal rate, safety RM separate from helpfulness RM.

Refuse to ship RLHF-PPO without a KL monitor. Refuse to use an RM smaller than the target policy. Refuse length-only rewards. Flag any pipeline that does not hold back a blind human-eval set as lacking over-optimization protection.