2026-10-11 18:02 UTC

Independent use will determine whether Sillage’s roughly 4MB memory layer gives frozen language models useful persistent memory with negligible deployment overhead.

state: expiredheat: lowuncertainty: highknownscott: lowpersistent-memory agent-memory local-inferenceriscoss63

What is this?

Sillage is presented in the supplied case as a roughly 4MB persistent-memory layer for frozen language models, associated with the handle riscoss63. The broader snippets support the need for external, structured memory layers to reduce context-window and token overhead, but they do not directly document Sillage’s architecture, benchmarks, creator, or real-world performance. Its claimed usefulness and negligible deployment overhead therefore remain to be established through independent evaluation.

Why it matters to Scott

Scott already holds the relevant position in `long-running-agents` and `context-engineering`: useful persistence should live outside frozen/stateless models and earn its place through compact state and retrieval evidence. Sillage is currently only another unvalidated implementation of that pattern; without architecture, benchmarks, or independent results, it does not yet alter his local-inference or memory-system practice.
ip:framework.long-running-agentsip:framework.context-engineeringdev:concept.trace-backed-agent-comparisondev:concept.hardware-aware-local-inferenceradar:concept.agent-memoryradar:memory-bench-layer-baseline-validityradar:self-written-notes-reasoning-gainsradar:concept.memory-efficiency
queries asked of Scott's wikis
  • agent memory architecture and persistent state
  • structured memory versus raw context injection
  • memory-layer evaluation and retrieval benchmarks
  • local inference memory and resource constraints
  • agent-maintained wikis as long-term memory
  • frozen-model augmentation without fine-tuning

Measured heat

no measured readings yet — the hourly heat pass fills this in

How the heat travelled

no chain yet — the hourly chain pass fills this in

Evidence (2) — ⭐ canonical anchor

sourceobjectauthorscorecomments
🟧 hnShow HN: Sillage a 4 MB memory that lets a frozen language>model rememberriscoss20
🟧 echo.github ⭐Sillage is presented as a roughly 4MB memory layer that enables a frozen language model to remember.riscoss63——

Interpretation history

Decision trace