History

jx12n 6a937fc4bc feat(m12): multi-vector user preference modeling + ANN candidate-gen Add multi-vector preference entity (per-signal-type preference vectors with event-time decay) feeding ANN candidate generation in the query executor. - entities: multi_preference vectors + event-time-aware preference updates - query/executor: ANN candidate-gen + personalization/pipeline integration - storage/keys, db ops, state_rebuild: persist & rebuild multi-vector prefs - ranking: profile + builtins support for multi-vector scoring - tidal-server/config: expose multi-preference knobs - tests/bench: m12_preference_event_time integration + multi_preference bench - docs: multi-vector-preference research, ROADMAP/ARCHITECTURE refresh, legal/tidaldb-patent-proposal - .codex/agents: codex agent definitions - chore: gitignore tool-regenerated .agents/ mirror (doc-guard rejects it)		2026-06-23 09:52:36 -06:00
..
guides	feat(m11): cluster security (m11p7) + perf instrumentation floor	2026-06-13 01:25:35 -06:00
legal	feat(m12): multi-vector user preference modeling + ANN candidate-gen	2026-06-23 09:52:36 -06:00
ops	docs: refresh ops runbooks to the live rc7 / full-placement reality	2026-06-19 19:53:29 -06:00
planning	feat(m12): multi-vector user preference modeling + ANN candidate-gen	2026-06-23 09:52:36 -06:00
profiling	fix(m12p6): 6-bug k3s 3-shard cluster repair (rc8+rc9)	2026-06-16 22:34:21 -06:00
research	feat(m12): multi-vector user preference modeling + ANN candidate-gen	2026-06-23 09:52:36 -06:00
reviews	feat(m11): observability+ops (m11p8) + perf-sweep wave 2 T2	2026-06-13 09:17:49 -06:00
runbooks	docs: refresh ops runbooks to the live rc7 / full-placement reality	2026-06-19 19:53:29 -06:00
specs	feat(m12): vector retrieval G1/G2 — recall harness, ANN in RETRIEVE, index tuning	2026-06-14 11:07:09 -06:00
content-strategy.md	feat: complete Milestone 5 — full-text search, RRF fusion, and creator search	2026-02-21 23:53:16 -07:00
personal-briefing-beachhead.md	feat: M0p1 runtime skeleton, M0p2 tooling & diagnostics, m1p4 signal ledger	2026-02-20 20:32:00 -07:00
README.md	feat(m11): membership, snapshot install, and reseed (m11p5)	2026-06-12 19:55:54 -06:00
roadmap-to-cluster.md	feat(m11): sharding × replication + rebalancing (m11p6 L3-L5)	2026-06-13 18:23:43 -06:00

README.md

tidalDB Engineering Docs

The engineering documentation home. Top-level product docs (VISION, USE_CASES, SEQUENCE, ARCHITECTURE, API, QUICKSTART, CODING_GUIDELINES, thoughts) live at the repository root; everything below is the deeper engineering record.

This and the repo root are the two canonical doc homes. There is intentionally no per-crate doc mirror (no tidal/docs/). Edit the canonical file, never a copy.

Component specs — `specs/`

The authoritative component specifications (status: Implemented, M0–M8).

#	Spec	#	Spec
00	Architecture overview	08	Query engine
01	Storage engine	09	Ranking & scoring
02	Entity model	10	Feedback loop
03	Signal system	11	Schema
04	Relationships	12	Cold start
05	Cohorts	13	Concurrency
06	Text retrieval	14	Scale architecture
07	Vector retrieval

Planning — `planning/`

ROADMAP.md — milestones M0–M11, phase status, known gaps
roadmap-to-cluster.md — adopted M11 plan: gap analysis + phase specs taking the multi-process cluster from experimental to enterprise-grade (m11p1–p5 ✅; p6–p9 planned), grounded in the 2026-06-10 live stress-test baselines
PRODUCT_ROADMAP.md · architecture-review.md · roadmap-cohort-analysis.md · site-cohort-analysis.md
Per-milestone phase/task archive: planning/milestone-0,1,2,3,5,7,8,9,10,11,p/

Code reviews — `reviews/`

M0–M10 code review — 2026-06-07 — seven-dimension re-review, 88 verified findings
M0–M10 code review — 2026-06-08 — seven-dimension review, 142 findings (latest pass)
M0–M10 seven-dimension review — additional pass (2 BLOCKERs: signal-checkpoint trim, 30-day window)

Guides — `guides/`

Task-oriented, build-an-app docs (complements the root QUICKSTART.md and API.md):

Build a feed app — end-to-end TikTok/Reels-style "For You" feed, embedded and over HTTP
Embedding integration — wiring a real embedding model (OpenAI / Cohere / local) into the write + query paths
Server deployment — running the tidal-server HTTP service: config, auth, the served OpenAPI spec, Docker
Ranking-profile reference: ai-lookup/services/ranking-profiles.md — all 25 built-in profiles