# Gemini CLI review (compressed receipt)

Source lane:
- standalone `gemini` CLI
- model: `gemini-2.5-flash`
- mode: headless advisory / plan posture

## Strongest points
- Four-part failure model (write, classify, retrieve, surface) is the sharpest diagnostic.
- The discussion correctly moves beyond "just add decay" into salience estimation, memory typing, retrieval gating, and mention policy.
- "Good memory systems should know when to stay quiet" is the right center of gravity.

## Weakest points
- Decay is acknowledged but its concrete role inside the four-part failure model should be made more explicit.
- "Classify too crudely" needs practical examples so readers can see what typed memory means on the ground.
- `openclaw-mem` examples should be tied more directly to which failure mode they mitigate.

## Missing angles
- Cost / latency / complexity tradeoffs
- User control and explainability, not just editable memory text
- Adaptive personalization: how a system updates and retires interests over time

## Recommended arc
1. The problem: why LLM memory gets stuck and starts haunting future conversations
2. Strategic silence: move from maximizing recall to governing relevance and suppression
3. `openclaw-mem` as a practical lab for retention/activation split, repeat suppression, scope isolation, lifecycle, and receipts
4. Open questions: evolving interests, understandable memory behavior, consolidation as candidate generation, and scalable governance

## Thesis sentence
Effective LLM memory transcends recall. It needs strategic silence through salience estimation, nuanced classification, judicious retrieval, and context-aware surfacing.
