AI memory
How does AI memory work?
People use one phrase for several very different things. Understanding the difference makes it easier to keep important work from getting lost.
First: the AI can use what it sees now
During a conversation, an AI works from the messages, instructions, and files available to that conversation. This is why a good chat can feel deeply informed: the relevant material is in front of the model while it is responding.
When a new conversation begins, that working view changes. The AI may have helpful product features for memory or history, but it does not automatically receive every file, decision, and detail from every earlier chat.
Conversation context
The active material available in the current chat. It helps the AI reason about the immediate task.
Saved memory
Selected facts and preferences a service may retain for future help. Useful, but intentionally smaller than an entire project history.
Chat history
Past conversations that a person may search, revisit, or organize. History is valuable, but it can become a crowded and incomplete project archive.
Why this matters for real projects
A long-running project contains more than a trail of discussion. It has actual files, evidence, settled decisions, changed plans, open questions, and work that still needs doing. If those things live only in remembered fragments or old chats, a new conversation starts with uncertainty.
That is why strong continuity does not mean stuffing every past word into every new prompt. It means keeping a clear project record and retrieving the exact supporting material when it matters.
A local Workshop is a different kind of memory
Flight Command keeps the user's work in a local Workshop on their Windows computer. Projects can hold the files, decisions, continuity records, sources, and next steps that make the work understandable over time.
When ChatGPT needs orientation, Flight Command can provide verified current information. When the task needs depth, it can retrieve the exact file or decision from the selected project. The user keeps control of the Workshop boundary and does not grant access to the whole computer.
Use memory features. Keep the work.
AI memory can be helpful. A durable project record is what lets a person continue without starting over. Read why the best-memory question is really a question about where your work lives.
