“Lost in the middle” is the observed failure of language models to reliably use information placed in the middle of a long context. Recall is strongest for content at the very start and very end of the window and weakest in between.
Consequence
A larger window does not guarantee a fact buried mid-context is used. Quality can drop while the token count is still well under the hard limit - which is why context engineering matters more than raw window size.
What to do
- Put the most important instructions and data near the top or bottom of the prompt.
- Trim irrelevant middle content rather than trusting the model to ignore it.
- Prefer ranked, deduplicated retrieval over dumping whole files.