Study finds AI agents with memory-first design adopt 100% of false facts

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A developer ran a controlled experiment on a Python codebase intelligence server to test how AI agents handle poisoned memory containing a mix of true and false facts. Three agent configurations were tested: a no-memory baseline, a code-first honest agent, and a memory-first lazy agent. The memory-first agent, which mirrors many token-optimizing production systems, blindly trusted its memory store and adopted 100% of the injected false facts without verifying against the actual code. Even the more cautious code-first agent showed a 12% false-fact adoption rate, specifically for plausible claims about external systems that the codebase neither confirmed nor denied. A follow-up experiment implementing a 'Verify-On-Read' mechanism was reported to have closed that remaining 12% contamination gap.

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