Why does graph maintenance fail?

The most common reason graph maintenance fails: Treating your graph as a write-only system — always adding, never reviewing. You accumulate nodes and edges without questioning whether they still reflect your actual understanding. The graph grows in size while shrinking in trustworthiness. Eventually you stop consulting it because the signal-to-noise ratio has collapsed, and you revert to keeping everything in your head — exactly where you started.

The fix: Open your knowledge graph or note system. Pick one cluster or tag you haven't touched in 30+ days. Walk through every node and every link. For each node, ask: is this still accurate? For each link, ask: does this connection still hold? Delete or archive anything that has decayed. Add any connection that should exist but doesn't. Track your counts: how many dead links did you remove? How many missing connections did you add? That ratio tells you how fast your graph is drifting from reality.

The underlying principle is straightforward: Periodically review and clean your graph — remove dead links and add missing connections.