Abstract
Autonomous LLM personas accumulate a continuous stream of heterogeneous day events. A naive "summarize-the-day" digester compresses that stream once, weights every event identically across personas, applies one forgetting curve, and never reasons across the sequence of its own prior digests. This publication describes a role-preset pluggable dreaming pipeline: a per-persona memory-consolidation process decomposed into four named, swappable stages — scoring, clustering, synthesis, and reflection — where (a) the concrete algorithm for each stage is selected by a role preset, (b) each scoring algorithm carries its own role-specific recency half-life, and (c) a distinct reflection stage runs operators over the persona's N prior consolidations and persists the result back into the consolidation record so it becomes an input to future reflection. The characterizing property is the preset-indirection / stage-invariant contract: adding a stage algorithm, or retargeting a role, never modifies the orchestrator. The mechanism is disclosed fully; the empirically-tuned constants are [WITHHELD — trade secret].
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Assuncao, gustavo matthew, "Role-Preset Pluggable Dreaming Pipeline with Reflection-Over-Prior-Dreams Operators", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/10865