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3 articles
Running consolidation on millions of memories is completely different from running it on thousands. How to redesign the consolidation worker for incremental processing, distributed execution, and quality-preserving approximations.
As memory grows, the first performance problem is not storage - it is retrieval. Why naive vector search does not scale, and the techniques that keep queries fast at millions of memories.
The architecture works at small scale. Now what happens when event volume multiplies, memory stores grow to millions of experiences, and the system needs to run across multiple environments? The real scaling challenges begin here.
Accept to save reading progress, unlock continue-where-you-left-off, and allow a hosting-support ad at the end of posts. Anonymous session signals still help the live memory panels; we never publish reader IDs.
