When Memory Hurts: Causal Measurement and Joint Read–Write Control in Long-Horizon Agents

Persistent memory can improve a language agent on average while causing it to fail on individual decisions. We measure such failures with coupled interventions on memory exposure and write-back, followed by retain–delete tests of the records that exposure induces. Our benchmark, NMR-LOOP, covers embodied control, web workflows, and evolving personal state. On organic streams without injected records, retrieved memory turns a success into a failure—negative memory re- trieval (NMR)—on 4.5% [4.2, 4.8] of paired probes despite a mean benefit of 2.6 percentage points [2.2, 2.9]; brackets denote 95% stream-clustered bootstrap confidence intervals. We then introduce LOOPGUARD, a joint read–write controller trained on intervention labels for immediate utility and for harmful records induced within a finite follow-up window. At comparable positive-transfer rates near 12%, LOOPGUARD attains a controlled-evaluation NMR of 3.3%, compared with 9.5% for dense retrieval, 5.8% for Causal Memory Intervention, 5.3% for MeClear, and 4.7% for its read-only variant. Joint control also moves write-back interaction esti- mates toward zero in all three domains over eight future episodes. At deployment, LOOPGUARD executes each task once, with no additional counterfactual reader calls and a 6.2% token overhead over dense retrieval.