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ShrimPK Backlog

Tracked items for the ShrimPK kernel project. Updated after each sprint. Source of truth for the ShrimPK kernel project.

Status Legend

  • DONE — shipped and tested
  • PLANNED — scheduled for a specific sprint
  • BACKLOG — accepted, not yet scheduled
  • RESEARCH — needs investigation before scheduling

Sprint Roadmap (KS73-KS80)

  • KS73: Entity unification — EntityFrame, UUID v5, alias store, entity supersession (PR #10)
  • KS74: LME micro-benchmark suite + evaluation pipeline
  • KS75: Runtime-configurable embedding model — EmbeddingProvider trait, 10 fastembed + OpenAI API (PR #14)
  • KS76: Universal prompt + temporal boost + importance scoring (PR #15)
  • KS77: KU-3 fix + abstention calibration — 19/20 seeded, 5/5 abstention (PR #17)
  • KS77b: Design system foundation + P0 graph polish — Tailwind 4.0 @theme, 6 components, 10 micro-improvements (PR #18)
  • KS78: Critical bug fixes — persistence format (#16), recency test panic (#13), supersession demotion (#11)
  • KS79: Multi-resolution retrieval — PPR-weighted Hebbian, fallback cascade, retrieval modes
  • KS80: Memory lifecycle — merge operation, soft-deletion compaction, multi-granularity storage

HIGH — Retrieval Quality

Components exist, need wiring. Validated by academic research.

  • PPR-weighted Hebbian traversal — Personalized PageRank seeded on echo hits, weighted by edge strength x ACT-R. +20% multi-hop QA (HippoRAG, NeurIPS 2024)
  • Multi-resolution retrieval fallback — memory → label cluster → community summary cascade. All three layers exist, not connected as fallback chain (RAPTOR, ICLR 2024)
  • Retrieval mode parameter — expose naive/local/global/hybrid on echo API (LightRAG, EMNLP 2025)
  • Citation-weighted memory scoring — track which injected memories LLM actually cites in response, upweight high-utility memories. Proxy already intercepts responses (RMM, ACL 2025)

HIGH — Memory Lifecycle

  • Merge operation — explicit ADD/UPDATE/DELETE/NOOP diff during consolidation. All production systems converge on merge as required (Mem0, RMM, Think-in-Memory)
  • Multi-granularity storage — tag memories by scale: utterance/turn/session. +10% LME accuracy (RMM paper)
  • Write-path learned filtering — decide what NOT to store before embedding. Most underresearched area per 2026 survey (arXiv 2603.07670)
  • Soft-deletion compaction — GC when FSRS strength drops below threshold. Currently decay only de-ranks, never removes (MemoryBank pattern)

HIGH — Cortex Prerequisites (blocking v0.10.0)

  • Inter-layer protocol design — Soul ↔ Brain ↔ Memory API surface. Direct Rust calls vs Tokio channels vs message types
  • Security model for agentic stack — data safety layer, poisoned memory detection. Distinct from command-level Brainstem
  • Alpha/Beta ARC competition model — formal design doc. Async parallelism, leader election, Adaptive Resonance Theory mapping

MEDIUM — Model & Format Upgrades

  • Nomic Embed Vision v1.5 — CLIP ViT-B/32 → Nomic, +7.8pp ImageNet zero-shot, 6x smaller ONNX. Breaking: 512→768 dim migration
  • f16 quantization for vision/speech — SHRM v3, ~50% disk/RAM savings, f32 promotion at query time
  • Band-limited resampling — replace resample_linear() with rubato crate. Correctness bug: aliasing at 48→16kHz
  • BuiltinConsolidator — bundled extraction model, zero Ollama dependency for consolidation quality
  • Configurable embedding provider — EmbeddingProvider trait, 10 fastembed models + OpenAI API (KS75, PR #14)

MEDIUM — Graph & Entity

  • Retroactive link invalidation — when A supersedes B, downweight ALL B-anchored Hebbian links, not just B itself (A-MEM/Zettelkasten pattern)
  • Episodic anchoring — bidirectional indices linking Hebbian edges back to source episodes (Graphiti/Zep pattern)
  • Entity-cluster summaries — entity-level community nodes, not just label-level (Graphiti temporal KG)

MEDIUM — Viz & UI Polish

Current state: Tauri 2 + Sigma.js 3.0 + ForceAtlas2, 3-level zoom (KS65-66). Functional but early MVP.

Graph Polish:

  • Smooth view transitions — animated node repositioning between galaxy/cluster/neighborhood (currently hard-resets layout)
  • Louvain community visualization — color nodes by community, show boundaries (graphology-communities-louvain installed, unused)
  • Edge labels on hover — show typed relationship (CoActivation, WorksAt, PrefersTool, etc.)
  • Temporal slider — filter graph by time range, animate memory formation over time
  • Custom node shapes per category — distinct shapes for Identity/Fact/Preference/ActiveProject/Conversation
  • Entity super-nodes — render EntityFrame nodes at graph level, not just label clusters
  • Node size by echo frequency — proportional to retrieval count, not just importance score

Memory Curation:

  • Inline memory edit — edit content/labels from detail panel, PATCH endpoint on daemon
  • Memory merge — select 2+ nodes, merge into one (new daemon endpoint)
  • Manual link creation — create Hebbian edges from graph view (new daemon endpoint)
  • Retag from graph — drag-drop between clusters or multi-select retag
  • Bulk operations — multi-select for delete/retag/export

Export Formats:

  • JSON export per memory — full metadata + embeddings + graph edges
  • Graph export — GraphML/GEXF for external visualization tools

MEDIUM — Quantization (v0.8.0)

  • Int8 scalar quantization (4x compression, simsimd ready)
  • TurboQuant integration (turbo-quant crate, 8-10x)
  • Binary + float32 rescore pipeline

MEDIUM — Intelligence Tuning

  • Full ACT-R retrieval history (Vec ring buffer)
  • ACT-R activation ON by default (after benchmarking)
  • Three-tier store (hot/warm/cold)
  • Importance retrieval boost (A/B test, then enable)

MEDIUM — Product & Distribution

  • Memory file export as .md sidecars — per-memory files with YAML frontmatter (distinct from bulk shrimpk dump)
  • Cloud sync — encrypted cross-device memory, E2E encrypted, server sees only ciphertext
  • Managed API planning
  • Revenue model implementation

MEDIUM — Benchmarks Not Yet Running

  • LoCoMo benchmark
  • MemoryAgentBench (ICLR 2026) — contradiction/conflict resolution focus
  • EverMemBench (2025) — entity disambiguation focus

LOW — Backlog

  • Memory as weights prototype (PyTorch via shrimpk-python)
  • Cluster summary tree (MemTree pattern)
  • Custom fine-tuned embedding model
  • crates.io publish (after API stabilizes)
  • Code signing certificate
  • PostToolUse async hook
  • Predictive coding layer — surprise/prediction error signal (~300 lines Rust)
  • Session-level dynamics tracking (COMEDY pattern — user-bot relationship)
  • Emotion channel — Apache 2.0 ONNX model needed (slot reserved in SHRM)
  • CAM++ speaker model upgrade — needs Apache 2.0 ONNX verification
  • SigLIP 2 vision model — needs upstream ONNX availability

RESEARCH — Long-horizon

  • Causal retrieval — retrieve by causal relevance, not just similarity (2026 survey frontier)
  • Model weight printing — cross-model knowledge transfer via externalized Hebbian weights
  • PyTorch cross-attention memory module — ShrimPK as transformer memory (v1.0+ ML stage)
  • GAAMA paper (arXiv 2603.27910) — concept-mediated KG with 4 node types, very close to ShrimPK architecture
  • Reflexion pattern — self-improvement via failure memories (Shinn et al. 2023)
  • Interleaved replay during sleep consolidation — novel-familiar mixing (neuroscience pattern)
  • EWC (Elastic Weight Consolidation) — prevent catastrophic forgetting in Hebbian updates (Nature Comms 2025)

Sync Issues (fix before next release)

  • docs/ROADMAP.md stale at v0.5.0 — update to reflect v0.7.5 state
  • CHANGELOG.md stops at v0.7.0 — missing v0.7.1 through v0.7.5
  • MCP tool count inconsistent across docs (12 vs 14)

Last updated: 2026-04-10