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Context Window Management
Surviving Long Horizons
Even with 1-million token context windows, an agent running for hours will run out of space or suffer from the "Lost in the Middle" phenomenon (where it ignores instructions in the middle of a huge prompt).
Compaction & Distillation
When the context grows too large, the Orchestrator pauses the agent, passes the history to a summarization model, and replaces the massive history block with a dense summary.
# Before Compaction: [Msg1 ... Msg100] (50k tokens) # After Compaction: [Summary_Msg, Msg95... Msg100] (2k tokens)
⌨ HANDS-ON LABExecute Recursive Context Compaction
⭐ +150 XPExecute context compaction and recursive summarization on an agent's conversational trajectory to prevent token overflow.
1Trigger memory compaction pipeline to compress conversation turns into a distillation summary.
OBJECTIVE 1 / 1 — type "hint" if stuck
SYNAPSE VERIFICATION
QUERY 1 // 1
What is the 'Lost in the Middle' phenomenon?
When an API connection drops halfway through
When an LLM fails to retrieve or recall information placed in the middle of a massive context window
When an agent deletes its own memory
When vector search returns 0 results