AI agents can extract attachments using personal context
Many AI tools handle attachments by pulling out broad, generic information because they do not know what the user actually needs. Without a clear instruction, the result can stay shallow.
This approach builds a from what the user has saved before, what those items were connected to, and why those links mattered. When a new attachment is uploaded, agents use that to choose what is worth extracting for that specific user.
If the user gives a direct instruction, that instruction takes priority over the stored context. After , the context is used again to connect the new material with the user’s existing captured information.
Key points
- Generic attachment often misses what matters to a specific user.
- Agents can use past saved items and links to decide what to extract.
- Direct user instructions override the stored context.
- The extracted material is connected back to the user’s existing information.
- This could make file-handling agents more useful and may reduce .