Context Management & Memory

Estimated time: 3 minutes

Context window = a finite, shared resource. Everything in a session competes for the same space: system instructions, conversation history, any retrieved or uploaded content, and the model's own output. It's not just "how much text can Claude read" — it's a budget that gets spent across the whole interaction.

Signs of context strain:

  • Degraded recall of earlier parts of the conversation
  • Repetition or circling back to points already covered
  • Drift — responses gradually losing thread of the original task

Mitigations:

  • Start a fresh session for a genuinely new task rather than stretching one thread indefinitely
  • Summarize and carry forward only what's load-bearing, rather than the full history
  • Use Projects to hold durable, recurring context outside the conversation itself, so it doesn't have to be re-established every session

Memory vs. Project knowledge — a distinction worth being precise about:

  • Memory features are what can persist information across separate sessions automatically, without you re-supplying it.
  • Project knowledge is context you deliberately attach to a Project, available to every conversation within it, but scoped to that Project rather than following you everywhere. They solve a similar problem (not repeating yourself) but at different scopes — one is automatic and cross-session, the other is deliberate and Project-scoped.