Context LatticeBy Private Memory Corp
V3 Program

From fast memory to context efficacy at scale.

V3 focuses on one outcome: more correct agent outcomes per request. The plan combines latency, recall quality, runner interoperability, and safety gates across backlog issues #68 through #72.

See track breakdown View release journal
Program Intent

What V3 changes for application efficacy

  1. Reduce p95/p99 deep-read tails while preserving high-quality sources.
  2. Increase recall precision with code/context-aware ranking and stronger source telemetry.
  3. Expand external runner compatibility with safer contracts and richer task lifecycle signals.
  4. Ship all changes behind reversible flags with benchmark and security gates.
Efficacy Chain

How V3 improvements cascade through the app

Write speed up
  -> queue pressure down
  -> sink freshness up
  -> retrieval freshness up
  -> recall quality up
  -> deep-read timeout rate down
  -> agent completion reliability up
  -> application throughput and trust up
Roadmap Graph

Grouped tracks across issues #68-#72

                 +-----------------------------------+
                 | V3 Objective: Context Efficacy    |
                 +-----------------+-----------------+
                                   |
        +--------------------------+--------------------------+
        |                          |                          |
+-------+--------+         +-------+--------+         +-------+--------+
| Track A        |         | Track B        |         | Track C        |
| Performance    |         | Recall Quality |         | Agent Surface  |
| #69 + #72      |         | #70 + #72      |         | #68 + #71      |
+-------+--------+         +-------+--------+         +-------+--------+
        |                          |                          |
        v                          v                          v
 Adapter spikes             Enrichment/rerank          Runner + sidecar
 ANN/indexing               and source policy          contracts/events
        +--------------------------+--------------------------+
                                   |
                                   v
                       Security + benchmark + recall gates
                                   |
                                   v
                              Staged V3 cutover
Track Groups

Integration scope by domain

Track A: Performance + Deep Read Stability

Backlog reference: performance/deep-read track aligned to planning set #69 + #72.

Primary repos: swiftide, fastembed-rs, EmbedAnything, zvec, edgevec, trieve, helix-db, chroma, tantivy, quickwit, lancedb, RediSearch, meilisearch, infinity, milvus, usearch, mini-rag, LightRAG, qdrant/rust-client.

Reference tuning source: qdrant/qdrant (engine tuning patterns, not a new integration target).

Key output: lower p95/p99 latency and fewer deep-read timeouts without quality regression.

Track B: Recall Quality + Memory Semantics

Backlog reference: recall/memory quality track aligned to planning set #70 + #72.

Primary repos: codemem, codegraph-rust, subcog, shodh-memory, mcp-redis, mindsdb, graphrag-rs, mem0, rust-local-rag, krira-chunker, satoriDB.

Key output: better ranking precision and better detail-dive linkage from rollups to source files.

Track C: Runner Interop + Compute Backend

Backlog reference: runner/sidecar track aligned to planning set #68 + #71.

Primary repos: opencode, openclaw, ironclaw, unbrowse, MCP registry, litellm; runner targets OpenCode, Goose, Eliza; ANE sidecar route for M-series macOS.

Key output: broader runner support with strict contracts, better progress telemetry, and safe provider fallback.

Validation Gauntlet

Integration and test flow for every candidate

  1. Security preflight: commit pinning, sandboxed execution, dependency/license + secret scans.
  2. Adapter spike: feature-flagged integration only, no default-path replacement.
  3. Benchmark gate: p50/p95/p99, throughput, timeout rate, deep-read stress.
  4. Recall gate: saved recall eval + code-heavy quality regression suite.
  5. Canary gate: staged rollout with rollback profile verified.
Wave 1 · 2026-03-09 to 2026-03-22

Harness + interface foundations

  • Benchmark matrix extension and deep-read stress scenarios.
  • Feature-flag adapter boundaries for embeddings/ANN/retrieval sources.
  • Security gates normalized across candidate spikes.
Wave 2 · 2026-03-23 to 2026-04-12

Performance and recall spikes

  • Track A candidate benchmarks and keep/drop decisions.
  • Track B enrichment + rerank prototype validation.
  • Publish artifacts and recommendation memo.
Wave 3 · 2026-04-13 to 2026-05-03

Runner and compute canary

  • Runner contract unification and lifecycle event telemetry.
  • ANE sidecar canary (M-series macOS) with automatic fallback path.
  • Interop hardening across OpenCode/OpenClaw/IronClaw surfaces.
Wave 4 · 2026-05-04 to 2026-05-24

Cutover readiness

  • Cross-track regression pass and rollback drills.
  • Final quality/performance sign-off against acceptance gates.
  • V3 release packaging and runbook publication.