Valley of Meh

The early-to-middle prompt region where in-context recency and lost-in-the- middle effects combine so context is used less effectively than at the edges.

Two placement effects stack in long prompts:

• In-context learning recency — information nearer the end of the prompt has more impact on the next tokens (in-context learning).
• Lost in the middle — beginning and end are recalled more reliably than the stuffed middle.

Together they create a Valley of Meh: an early-to-middle band where context is under-used. Depth and location vary by model, but every long prompt has one. Mitigate by placing key, high-quality elements outside the valley, filtering for conciseness under context engineering, and using the sandwich technique so the task is restated after the context parade. There is no perfect fix — keep prompts short enough that the valley cannot swallow the payload.

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Sources

• Prompt Engineering for LLMs (Berryman), ch. 6