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AI agents that ace isolated coding tasks fall apart when faced with the messy reality of continuous software evolution, dropping from 80% to 38% success rates in a new benchmark.
Current LLM memory systems falter when faced with the continuous, machine-generated interaction streams typical of real-world agentic applications, highlighting a critical need for causality-aware and tool-augmented memory architectures.
