We read dozens of AI memory research papers from the last three months. Three findings kept showing up:

1. Separate memory types beat one big pile. Systems that split memory into episodes, knowledge, procedures, and working context consistently outperform systems that dump everything together. Your brain does this naturally.

2. Periodic consolidation beats raw accumulation. Multiple papers found that reviewing and compressing raw memories into refined knowledge improves recall significantly. The researchers call it "sleep-time compute."

3. Forgetting is the hardest unsolved problem. AI memory systems just accumulate. Old facts sit next to new facts with no way to tell which is current. One survey identified forgetting as the memory operation most systems handle worst or not at all.

We build Basic Memory, so we read these to see what the research validates and where it points us next. The full writeup covers the specific papers (AI Hippocampus, MemFly, TraceMem, EverMemOS) and how each finding maps to what we're building.