Fill-in-the-middle (FIM) generates code for a middle section given surrounding context, enabling intelligent code insertion. Problem: Standard language models generate left-to-right, but coding often requires inserting code between existing code. FIM training: Rearrange code sequences: PREFIX + SUFFIX leads to MIDDLE. Model learns to generate appropriate middle given surrounding context. Format: Special tokens mark sections: prefix code, suffix code, then model generates middle. Why it helps: Better function body completion (given signature and usage), infilling documentation, implementing interface methods, completing partial code. Model support: CodeLlama, StarCoder, DeepSeek-Coder, Codestral trained with FIM objective. Some models need specific FIM fine-tuning. IDE integration: Copilot-style completions that consider code after cursor, not just before. More natural insertions. Evaluation: Different from standard left-to-right, measure exact match and functional correctness for FIM tasks. Related techniques: Infilling for text, span corruption (T5), prefix-suffix-middle variants. Impact: Significantly improves code completion quality in real editing scenarios. Standard feature in modern code models.