Memory Augmentation
Definition
AI applications supplement the current dialogue with stored information.
Additional memory holds conversation history, preferences, or work results for later retrieval. Retrieval rules decide what actually enters the model context.
Simply explained
An assistant uses an organized notebook instead of starting each conversation anew.
Why it matters in practice
Continuity can avoid repetition and support multi-step tasks.
Example from business
Hypothetical example: A project assistant remembers approved writing rules for later drafts.
Limits and pitfalls
- Outdated or incorrect memories can persist. Storage requires clear deletion and access rules.
Origin & history
The approach combines dialogue state and external memory with language model applications.
Use in mid-sized companies
- SMEs can make project-related knowledge selectively available without sending everything permanently.
Frequently asked questions
Does the model learn new weights in the process?
Usually not, it receives additional context data.
Sources
- Sessions — · OpenAI Agents SDK: Sessions —
Editorially reviewed on: