Problem
Long conversations can exceed the amount of information an AI model can use at once. Earlier details may be dropped or summarized without people realizing it.
Solution
Show how much of the model’s available context is in use. Explain that messages, attachments, and instructions share this space. Use a readable measure, such as a percentage, with technical details available separately.
Warn people while they still have room to act. Offer relevant options, such as removing a large attachment or starting a new conversation with a summary.
When earlier messages are summarized or removed from context, mark that change in the conversation. Explain what the assistant can still use. Show when an attachment takes up a large share of the available space.
Use when
Conversations run long, include large documents, or use models with different context limits.
Don’t use when
Exchanges are short and self-contained. A meter that never moves off empty is decoration, and it teaches people to ignore an indicator that would matter later.
Trade-offs
A meter helps explain forgotten details but asks people to manage a technical limit. Summaries keep conversations going while losing some detail. A percentage is easier to understand than a token count, but it cannot show exactly how much more work will fit.
Checklist
- Does the viewer learn the window is filling before it is full?
- Is there a visible marker where earlier turns stopped being included?
- What’s the overflow behaviour, and is it stated anywhere a viewer would look?
- Does a large attachment show its share of the budget?
- Are the units something a person can act on?
- Does switching models change the limit visibly?
- Is there a one-click way to continue in a fresh conversation with a summary?
- Do standing instructions count against the budget, and is that visible?
- What happens to a branch abandoned by an edit, and does it still occupy space?
- Does the assistant say when it can no longer see something it was told?
Compare
Claude publishes its window sizes per model and ties the limit to the model choice, so the constraint is a documented property rather than folklore. ChatGPT mostly hides the meter and manages overflow behind the scenes. The interface stays calm and the forgetting gets harder to attribute. Gemini competes largely on window size, which turns the limit into a marketing surface and reduces the need for an in-product meter. Cursor takes the opposite approach for a technical audience and shows what is in context as an explicit, editable list. The budget becomes something to curate rather than something the product hides.
Related
Conversation history preserves earlier sessions even when their full text no longer fits in context. Attachment tray shows files using that space.
Usage meter tracks a separate usage allowance. Scoped context selects the material available to the assistant. Custom instructions also use context space.