A compiler approach to agent logs that reduces token consumption by 50-66% while improving context learning performance.
April 1, 2026
Original Paper
View-oriented Conversation Compiler for Agent Trace Analysis
arXiv · 2603.29678
The Takeaway
By treating agent conversation traces as structured data to be compiled into specific 'views,' it significantly optimizes the context window and improves the reasoning quality of reflecting agents.
From the abstract
Agent traces carry increasing analytical value in the era of context learning and harness-driven agentic cognition, yet most prior work treats conversation format as a trivial engineering detail. Modern agent conversations contain deeply structured content, including nested tool calls and results, chain-of-thought reasoning blocks, sub-agent invocations, context-window compaction boundaries, and harness-injected system directives, whose complexity far exceeds that of simple user-assistant exchan