Lesson 2061 of 2116
Context Windows, Lost in the Middle, and Practical Limits
Long-context models still forget the middle — and how to design around that.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2context windows
- 3lost in the middle
- 4retrieval
Concept cluster
Terms to connect while reading
Section 1
The premise
Models advertise million-token contexts, but research shows performance degrades for content placed in the middle of long inputs. Design your prompts knowing this asymmetry.
What AI does well here
- Putting the most important instructions at the very start AND the very end
- Chunking and retrieving relevant passages instead of dumping whole documents
- Verifying recall against specific facts placed deep in long inputs
- Using structured headers so the model can navigate long inputs
What AI cannot do
- Treat a 1M context as a perfect, uniform memory
- Eliminate the cost of processing very long contexts
- Know exactly which sentence the model attended to in producing an answer
Key terms in this lesson
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