ChatGPT Go Users Report Memory Feature Glitch Amid Widespread Complaints

Users of OpenAI’s ChatGPT Go subscription service are increasingly reporting a persistent and frustrating glitch: the AI’s memory feature, designed to retain conversational context across sessions, is spontaneously and inexplicably turning itself off. The issue, first highlighted in a Reddit thread by user /u/itzmrbonezone, has since garnered hundreds of similar reports from subscribers who say they are unable to maintain memory activation—even after manually re-enabling it. The feature, which allows ChatGPT to remember user preferences, past interactions, and personal details, is a cornerstone of the premium experience, making its instability a significant concern for power users and professionals relying on continuity.

While OpenAI has not issued an official statement regarding the issue, technical analysts suggest the problem may not be a simple bug but rather a symptom of deeper architectural conflicts. Memory functionality requires persistent data storage tied to user accounts, which must sync across devices and sessions. According to linguistic and technical usage patterns documented in English Language & Usage Stack Exchange, the term "issue" in software contexts often refers to a systemic malfunction rather than a one-time incident. This aligns with user reports indicating a recurring pattern, not an isolated error. The word "issue," derived from Latin issus meaning "a going out," evolved in the 20th century to denote a problem or point of contention, particularly in technical and organizational discourse—making its use in this context both semantically accurate and culturally embedded in tech communities.

Further complicating the matter is the lack of transparency in how memory settings are managed. Users report enabling the feature through the app interface, only to find it reverted upon next login or after a brief period of inactivity. This behavior suggests either a server-side override, a conflict with privacy policies, or an unintended auto-reset triggered by data hygiene protocols. In software development, such behavior is often described as "triaging an issue," a term borrowed from medical triage and adopted by tech teams to prioritize and categorize bugs based on severity and impact. As reported on English Language & Usage Stack Exchange, triaging an issue involves diagnosing root causes, assessing user impact, and determining whether the problem stems from code, configuration, or policy. The widespread nature of these reports indicates this issue has already entered triage queues at OpenAI.

For users, the implications extend beyond inconvenience. Professionals using ChatGPT Go for client communications, content planning, or research depend on memory to maintain context across days or weeks. When the feature resets, it forces users to re-explain their needs repeatedly, undermining efficiency and trust in the service. Some users have resorted to manually documenting their conversations externally, a workaround that defeats the purpose of the premium feature.

OpenAI has previously emphasized its commitment to user privacy and data control, and it’s possible the memory feature’s instability is a side effect of cautious data retention policies. However, the absence of communication from the company has fueled speculation and user frustration. Without clear guidance on whether the behavior is intentional, temporary, or a bug, users are left in limbo. The pattern of recurrence, combined with the lack of transparency, suggests this is more than a minor glitch—it’s a credibility issue for a product positioned as a reliable, intelligent assistant.

As the demand for AI memory grows—especially in enterprise and educational applications—this glitch could signal broader challenges in balancing personalization with privacy. OpenAI’s next move will be critical: either a swift fix with public acknowledgment, or a policy change that clarifies the limits of memory retention. Until then, ChatGPT Go subscribers remain in the frustrating position of being unable to trust the very feature they paid to use.