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?
Direct matches only
Direct matches plus one connection
Follow several connections when confidence is high
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.
Replies
I’d default to direct matches + one strong connection. Memory is useful when it brings back the context that changes the decision, not when it shows every related thing it can find. the best AI memory should feel like judgment, not search results with extra steps.
For a default setting, I’d lean towards #2 (Direct matches plus one connection). As a founder, I usually just need the immediate answer and maybe the most recent pivot. Anything deeper than one connection tends to add mental friction when I'm just trying to move fast.