C2-a surfaced contemplation runs but rendered each scene as a flat JSON dump —
outputs, not process. C2-b makes the loop legible: every scene is now a typed
stage in the canonical ADR-0172 arc.
Reader-first (no theater):
- schemas.py: ContemplationScene gains a typed loop projection — stage_role
(cold_attempt | engine_enrichment | engine_proposal | operator_ratifies |
grounded | other) plus the connective ids (proposal_id, candidate_id,
proposal_state, grounding_source). New ContemplationStageRole Literal.
- readers.py: _contemplation_scenes derives stage_role from the scene id
(closed set, "other" fallback) and pulls the connective ids out of the raw
detail. schema-snapshot.json regenerated.
UI:
- ContemplationRoute: the run detail now renders the arc as a staged process —
"attempt → enrich → propose → ratify → grounded" with named stage roles,
cold→grounded bookends (surfaces pulled out of before/after), the connective
ids as evidence, and the raw detail tucked into a collapsible (not lost).
Honest wrinkle (surfaced, not faked): the fixture proposals do NOT resolve in
the live proposal log (source_kinds exemplar_corpus/operator, none
contemplation), so the proposal id is shown as evidence but is intentionally
NOT a clickable cross-route link — a dead link would be theater. Live
Proposals/Calibration navigation is deferred to reader-verified linking once
real contemplation proposals reach the log.
Validation: 128 workbench Python tests + new reader-projection tests (canonical
arc → roles, unknown → "other", id extraction, detail preserved); 466/466
frontend incl. schemaDrift + the staged-process / no-dead-link test; pnpm build
clean; git diff --check clean. No serving-path imports.
Makes the CL(4,1) field geometry legible, honestly. The engine owns the field;
this surfaces ONLY the exact scalar invariants it computes — never the raw
multivector — so the workbench shows "this is the geometry, it's exact, it
can't fake coherence" without a decorative blob or any motion.
Persist-first (the C3 gating work was Python, not React): the honest scalars
were computed live per turn but discarded. Now captured per turn into the
journal so a read-only surface has real evidence.
Backend:
- workbench/field_evidence.py: FieldEvidence computed from the engine result —
exact versor_condition, field_valid (vs the 1e-6 ceiling), a content-
addressed field_digest (sha256 of the engine-canonical array bytes), and
cga_inner(before, after) as the exact transition value. Raw field bytes
never cross the boundary: only floats + digests. validate() is fail-closed —
field_valid can never disagree with versor_condition vs the ceiling (the
wrong=0 analogue for the geometry). No engine math re-implemented
(versor_condition / cga_inner imported from algebra; bytes via array_codec).
- workbench/schemas.py: FieldEvidence dataclass; field_evidence on
ChatTurnResult + TurnJournalEntrySchema. schema-snapshot.json regenerated.
- workbench/journal.py + api.py: persisted at from_chat_turn; first-class read
endpoint GET /trace/{turn_id}/field (trace facet, consistent with /pipeline).
- workbench/replay.py: field_evidence classified CRITICAL — replay now also
proves field determinism (digest + scalars must match on re-execution).
Frontend:
- types/api.ts FieldEvidence + field_evidence passthrough; client/query hook;
FieldInvariantCard (measured value vs ceiling, cga_inner transition, digests;
honest missing_evidence; no blob, no motion); Trace route Field tab.
Honest-empty for pre-widening journal rows (missing_evidence). Deferred:
cross-turn field-coherence trends, session-level field persistence.
Validation: 138 workbench/practice Python tests (incl. non-vacuous field guards
+ replay field-determinism); 465/465 frontend incl. schemaDrift; pnpm build
clean; git diff --check clean. No generate.derivation / reliability_gate /
stream / field.propagate / vault.store imports.
Lands the Phase C "make cognition legible" slice plus Phase A residue, all
backend-reader-first over real engine data (no theater, read-only doctrine
intact, zero serving-path imports).
C1-a — Cognitive pipeline record (persistence-first, per #729 worthiness edit):
- workbench/pipeline_record.py: curated CognitivePipelineRecord over the real
CognitiveTurnResult (input → intent → proposition_graph → articulation_target
→ realizer → walk_telemetry → trace_hash). Raw field multivectors are
DELIBERATELY excluded; _assert_no_raw_field_payload recursively rejects raw
field keys, and validate_pipeline_record fails closed on missing/duplicate
stages, non-recorded status, or dangling edges — the UI can never receive a
partial record that claims to be complete.
- test_workbench_pipeline_record.py: non-vacuous guards — missing stage,
monkeypatched new required stage, and injected raw {"F": [...]} each raise.
C2-a — Contemplation as a process: /contemplation route over real persisted
contemplation/runs/*.json (glob reader; honest-empty when absent).
C4-a — Identity continuity (L10/L11): RunDetail.identity_continuity + Runs
Identity tab, sourced from the real core.engine_identity (engine_identity /
parent_engine_identity lineage relation, re-derived to verify).
Demo Theater: renders backend-owned proof-promotion + entailment DAGs.
Phase A residue: density preference wired end-to-end (settings → shell → tokens);
cross-route consistency touch-ups.
Infra: local API CORS now echoes only validated 127.0.0.1/localhost origins
(hostname-checked, not arbitrary reflection) so Vite fallback ports work.
Route chunk-split keeps the build warning-free.
Cleanup: corrected the stale ADR-0175 practice-lane assertions (build_report is
6 correct / 0 wrong / 44 refused after the current serving lane; wrong=0 held)
and the two registry-derived count tests (LeftNav + CommandPalette 12 → 13 for
the new Contemplation route).
Docs: runtime_contracts.md (pipeline-record contract), UI-UX-GUIDE,
api-contract-v1, data-shapes-v1, wave-M-worthiness, phase-a-residue-ledger.
Validation: 106 workbench/practice Python tests green (incl. wrong=0 lane +
pipeline-record fail-closed guards); 459/459 frontend; pnpm build clean;
git diff --check clean. No generate.derivation / reliability_gate / stream /
field.propagate / vault.store imports.
Two corrections from this session's source verification:
- B3.5 D2 (calibration artifact): coherence between report.json and
ratification_queue.json is necessary but NOT sufficient. The 95/50/5 earned
state is a fossil from the disabled resolve_pooled scorer (queue committed in
b82897a0); no current runner reproduces it (main()=6/44/0, candidate-graph
practice=0/1/149). Acceptance now requires report.json be byte-reproducible
by a documented deterministic runner pass; copying numbers between artifacts
is inadmissible. Three routes named (honest-floor now, earn-it-for-real
follow-up, defer).
- C1 (cognitive pipeline visualizer): corrected the false "reader-first over
existing telemetry" framing. Verified the journal persists only ~12 surface
fields of CognitiveTurnResult's ~25; no /trace/{id}/pipeline endpoint. C1-a's
real first deliverable is a persistence change: a curated
CognitivePipelineRecord (never the raw field_state multivectors — O(n^2)
cost), a runtime-contract update, and a non-vacuous fail-closed test.
The docs/proposal-artifact-substrate-v1 work (#727) — wave-m-consolidation-b3.5,
core-logos-studio-plan, proposal-artifact-substrate-v1 — is the authoritative
consolidation and supersedes the parallel 'Phase A' I'd just drafted. Reconciling
to one source of truth:
- FOLD IN the one genuine gap b3.5 missed (a design review caught it): the
Calibration centerpiece undersells — the reader reads the sub-N_MIN committed
practice report.json, so on live data no class shows licensed, while the
earned state (additive 95/5/100, PROPOSE-licensed) sits in the disagreeing
ratification_queue.json. Added as a diagnosis addendum + a Deliverable-2
acceptance criterion (make the committed practice artifacts coherent; show
≥1 earned class). Data-side fix, not a re-derivation.
- FOLD IN the grouped-navigation idea: a field on the route registry
(Deliverable 1) + the organism's-loop grouping (Converse/Cognition/Evidence/
Determinism/Discipline/Substrate/Settings), with the correction that
'core-logos' is the language/manifold Studio surface, not the cognition cluster.
- REDIRECT wave-M-worthiness.md's consolidation section to point at b3.5 instead
of defining a parallel Phase A.
- SCRAP duplicates: wave-M-phaseA-briefs (duplicated b3.5) and
workbench-ui-ux-guide-brief (superseded by b3.5 Deliverable 4).
Boils the design review and the information-architecture decision into one
integration. Phase B's heart (calibration/serving discipline) is done;
Phase A (Structure & Polish) now runs BEFORE resuming Phase C because two of
its items are structural prerequisites the Cognition cluster lands into.
Key synthesis: the command-palette drift bug and the grouped-nav idea are
the SAME fix — navigation derives from one registry that also encodes
structure. Standing IA constraint: one workbench, one address space, one
Chain Rail; grouping is a wayfinding skin, never an architectural fork; no
separate workbenches (the single evidence model is the thesis); 'levels' are
depth-within-a-surface, not top-level categories.
Phase A brief pack (wave-M-phaseA-briefs):
- A1: navigation registry (one source of truth) + grouped nav by the
organism's loop (Converse/Cognition=core-logos/Evidence/Determinism/
Discipline/Substrate/Settings) + palette fix (Demos+Calibration are
currently unreachable via ⌘K; the ⌘1-0 map is stale)
- A2: Calibration earned-state — the centerpiece undersells (reads the
sub-N_MIN report.json; the earned license lives in the disagreeing
ratification_queue). Primary fix: regenerate coherent practice artifacts;
fallback: reader surfaces both with provenance
- A3: Doctrine station ('how this UI can't lie') — elevate contracts/checks
into a first-class surface; trails, larger
Parked: B4 (needs engine-side license stamping; no re-derivation),
Calibration EvidenceSubject kind.
Wave M takes the workbench to mastery and closes its biggest design gap:
it surfaces the teaching/ratification loop but is blind to the
calibrated-learning / serving-discipline loop (gold-tether arena, reliability
gate, Wilson floor vs θ ceiling, 'the engine earns the right to guess') and
to cognition itself (pipeline stages, field substrate, identity continuity).
Lens: Anthropic + xAI as target users who'd WANT to use it.
- wave-M-worthiness.md: full plan, Phases A–E, the missing-surfaces table,
the backend-reader-first / never-re-implement-engine-math disciplines,
execution order (B→C→D, A parallel).
- wave-M-phaseB-calibration-briefs: executable Phase B pack grounded in the
real core/reliability_gate shapes (ClassTally / conservative_floor /
license_for / Action θ) and the committed report.json evidence — B1
readers (GATING, Python), B2 Calibration route, B3 wrong=0 global frame,
B4 leeway wiring. Dependency DAG + STOP gates + no-theater rules.
