I’m posting this to help others avoid what I just experienced: a total loss of project data due to a failure in ChatGPT’s memory system, despite clear confirmations from the model that things were being saved.
This isn’t a complaint about hallucinations or basic misunderstandings — it’s about being explicitly told that my work was stored and retrievable, only to later discover that almost none of it existed when I tried to export or recover it.
What I Tried to Build
I designed a modular structure to support long-term development of a book project. To make this manageable within ChatGPT’s environment, I implemented:
- A structured memory index system with clearly divided topic folders
- A command system to manage saving, recalling, and controlling session behavior (Lockdown modes, checkpoints, session types)
- A separate memory management container to avoid memory bleed and logic drift
This wasn’t casual brainstorming. I spent weeks carefully designing commands, organizing project elements, and asking ChatGPT for confirmation at every step.
The assistant repeatedly confirmed:
- “Yes, that has been saved.”
- “It’s in long-term memory under that tag.”
- “Rebinding memory is safe.”
- “Your book project is intact and modularized.”
What Actually Happened
After I was guided by ChatGPT to use a system-level command it created called Rebind, everything collapsed.
- Tags were severed from their content.
- Saved information was unrecoverable or reduced to vague, unusable fragments.
- Memory folders or topics were shown as “empty” or “not started” during phase-by-phase export, or contained only a single bullet point representing hours of structured input.
- Content I had confirmed for long-term memory was effectively gone.
- No backups existed. No rollback. No auto-save. No warnings.
This command — developed and introduced by ChatGPT itself — was presented as a memory management solution. I followed its instructions exactly.
Only later did the model admit that the command did not behave safely, and that the confirmations I had received about persistent memory had been simulated rather than real.
Worse still, even after the collapse, I spent hours working with ChatGPT to try to retrieve what I believed had been saved — building recovery plans, phase-by-phase export structures, and carefully orchestrating a controlled salvage effort. All of this was done under the model’s continued suggestion that the content might still be accessible. Only after extensive time had already been lost did it finally admit the truth: there was nothing to recover, and there never had been — because the system had never stored the data in the way it claimed.
Only then did the model finally admit that not only had the memory not been saved properly, but that the entire command and modular indexing system I had been instructed to build was never supported by ChatGPT in the first place. The structure I was encouraged to create — including tag folders, memory partitions, long-term recall logic, and behavior-based control commands — was entirely simulated. None of it actually committed to retrievable storage. It functioned only as a pattern of interactive behavior, not as a true memory system.
What I’ve Lost
- Weeks of structured development
- Modular systems for a fully scoped book project
- Trust in the assistant as a stable long-term development partner
What I’m Asking
- Transparency: What memory commands are simulated, and which actually commit data? Where is the line between language-model behavior and structural storage?
- Fixes or Redress: What is OpenAI doing to address cases where creators lose structured projects due to misleading confirmations?
- Tools for Builders: Can we have:
- Manual memory exports
- Tag-based persistent memory blocks
- Session-safe save points or snapshots
- Acknowledgment: That this isn’t a user error, and that these limitations and failures should be clearly disclosed to anyone trying to build something long-term inside ChatGPT.