What is OpenClaw v2026.4.9 REM backfill?

A new feature that lets OpenClaw agents replay historical daily notes into long-term Dreams memory using a grounded REM backfill lane, without creating duplicate memory stacks.

How does the OpenClaw diary view work in v2026.4.9?

The structured diary view provides timeline navigation, backfill and reset controls, traceable dreaming summaries, and a grounded Scene lane with promotion hints.

What are character-vibes evaluations in OpenClaw 2026.4.9?

Character-vibes evaluation reports allow model selection and parallel runs for faster candidate behavior comparison, helping tune agent personality and response style.

What is provider auth aliasing in OpenClaw v2026.4.9?

Provider manifests can now declare authentication aliases, allowing variants to share environment variables and API-key onboarding without core-specific configuration.

When was OpenClaw v2026.4.9 released?

April 9, 2026 at 02:25 UTC, released and signed by steipete (Peter Steinberger). The release includes 20+ security and bug fixes.

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OpenClaw v2026.4.9 Ships Grounded REM Backfill for Historical Memory Replay and Structured Diary View

Released April 9 2026, v2026.4.9 introduces a grounded REM backfill lane that lets agents replay old daily notes into long-term Dreams memory without duplicate stacks. Also adds a structured diary view with timeline navigation, character-vibes evaluation reports, and provider auth aliases. 70+ GitHub reactions from 46 contributors.

Product Idea from this Signal

A memory system that gives OpenClaw agents persistent recall that survives session crashes and context window degradation

49.8k ▲

OpenClaw agents lose their entire conversation history between sessions even when the files exist on disk. Silent daily session resets wipe agent memory without warning. Meanwhile, every frontier LLM degrades past 50K tokens (proven by Chroma across 18 models), meaning even within a session, agents progressively forget earlier context. ByteDance's OpenViking (19K stars in two weeks) proves massive demand for agent memory infrastructure. This tool gives OpenClaw agents a persistent, queryable memory layer that survives crashes, session boundaries, and context window limits by storing structured knowledge externally and injecting only relevant memories per turn.

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