Current large language models trained on GitHub code are excellent imitators but lack true engineering understanding because they only see final code versions. The author proposes training LLMs on the full commit history of projects, including commit messages, to expose the decision-making process behind code evolution. This approach could enable models to learn architectural reasoning, refactoring skills, and the 'why' behind code changes, transforming them from mere imitators into genuine engineers. AI
IMPACT Training LLMs on commit history could lead to more capable AI engineers with better architectural decision-making.
RANK_REASON The item is an opinion piece discussing a proposed method for training LLMs.
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