How far should an AI follow your memory graph?

One of the hardest decisions in Second Brain v2 was deciding how much related context recall should include.

Imagine asking:

"What did we decide about the Product Hunt launch?"

A normal search might find the launch plan.

A graph-aware system could also find:

  • the positioning decision connected to it

  • feedback that changed the launch date

  • the demo you created afterward

  • a previous community post that performed well

  • an older decision that has since been replaced

That can be genuinely useful. It can also become noisy very quickly.

Second Brain handles this by ranking direct matches first, then expanding through connected memories with distance decay. The further away a memory is, the more evidence it needs to appear.

I want the graph to recover context you forgot existed, without making every answer feel like a tour of your entire database.

Where would you set the default?

  1. Direct matches only

  2. Direct matches plus one connection

  3. Follow several connections when confidence is high

  4. Let the AI decide each time

Second Brain v2 is live today, and this is one of the areas where I would especially value feedback.

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