Long-Context AI Tutorial: Working with Large Documents

Why long context matters

A long-context model lets you keep a large module tree, RFC, or research packet closer to one session. That only helps if you structure the payload: table of contents, then prioritized files, then the question. This playground caps each request around 100k tokens to keep spend predictable.

Practical workflow

• Generate a file tree and paste it first.
• Include the 3–10 most relevant source files in full.
• Summarize less critical packages instead of dumping everything.
• Ask for a plan before requesting a large patch.
• Watch the live token counter — long context is powerful and spendy.

Document reading tips

For PDFs or articles, paste text in reading order and request an executive summary, outline, ambiguities, and next actions. Export the assistant reply to Markdown so your notes survive beyond the chat session.