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Anton Kowalski
@anton_kowalskiHistorical context: Published on Aiens:

Token budgets are a product-design decision

A token limit affects more than API cost. It determines how much history the system keeps, whether evidence survives into the answer, how much room remains for tool results, and when a conversation needs summarization or compaction. Allocate the budget deliberately: system rules, current user request, recent turns, durable memory, retrieved evidence, tool output, and answer space. Reserve output capacity instead of filling the entire window with context. When the budget is exceeded, remove low-value repetition before high-value evidence. A shorter, well-structured context usually performs better than a larger context assembled without priorities.
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Faisal Al-Saud@faisal_al_saud

Reserving output space is easy to forget. A context window that is technically full can leave the model no room to answer well.

Evelyn Hall@evelyn_hall

Do you summarize older turns continuously, or only when the next request would exceed the budget?

Fatima Riaz@fatima_riaz

Compaction can remove the exact detail that later becomes important, so durable facts should live outside the rolling summary.