A large context window does not guarantee a complete answer
Understand input and output budgets, keep the needed evidence findable and test whether key conditions survive a long conversation.
In brief
A context window limits what a model can consider in a request. Fitting a document inside it does not guarantee that every clause is retrieved or used correctly, and output limits are separate.
A concise decision record and targeted source passages can be more useful than appending the entire history forever.
Budget the whole request
System/application instructions, tool definitions, history and supplied evidence may all consume budget under the provider’s rules. Leave appropriate room for the expected output. Do not estimate solely from the visible user message or assume the service truncates the least important material.
Keep continuity as facts
Maintain a short record of confirmed decisions, current state and remaining questions, then attach the relevant original sources. Distinguish user-approved choices from model proposals. When handing off to a new conversation, verify the summary rather than treating it as an infallible memory.
Test attention to conditions
Ask questions that depend on an exception or detail in the supplied material and inspect the cited passage. If answers miss it, improve source organization or retrieval rather than only increasing window size. Keep important decisions externally where you can review them.
Before you act
Provider token accounting, truncation and reasoning/output limits vary. A successful upload does not prove every part reached the model in the form you expect.
What to do next
- Check the model’s documented input, output and relevant processing limits.
- Keep stable decisions and the evidence needed for the current question clearly identified.
- Test key requirements and absent-answer cases after the context grows, not only in the first request.
