Adding Project Memory to Claude Code Cut Its Error Rate from 52.5% to Zero
A developer tested Claude Code on 40 tasks drawn from real project history, comparing a standard session against one augmented with a curated memory tool called RE-call. Without memory, the AI made errors on 52.5% of runs; with memory, it recorded zero failures across all 40 paired trials. Answer correctness and factual accuracy both roughly doubled, and the memory-enhanced version never performed worse than the baseline in any single run. Each task contained a hidden pitfall — such as a command that appears to succeed but does nothing — that could only be avoided with knowledge of the project's past decisions. The experiment used deterministic checkers and repeated each task ten times per condition to account for the non-deterministic nature of AI agents, with p-values at or below 0.0003.
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