Lands the dynamic Team-memory redesign on top of main's continual-learning
pipeline. main already computes loop/activity in the API but its GraphView never
rendered them and kept a static-column graph; this swaps in the dynamic graph and
surfaces the rails, reusing main's richer PodLearningLoop / PodGraphActivity types.
Frontend (new frontend/src/components/graph/*, composed into GraphView.tsx):
- forceSim.ts: dependency-free force layout (charge, link springs, centroid
recenter, 2-pass collision, bounds clamp, alpha anneal) — no new deps/lockfile churn.
- GraphCanvas.tsx: SVG render from the sim — draggable + pinnable nodes, curved
edges, weight-sized shapes, fade-in, animated learned_from dash, risk-path
lighting / rest dimmed, label collision-avoidance.
- MetricsRail / LearningLoop / ActivityStream / SelectedNodePanel / encoding.ts:
the mock's rails + stream + detail panel in light shadcn. LearningLoop consumes
main's PodLearningLoop (steps + activeStep); ActivityStream consumes
PodGraphActivity (title + detail). SelectedNodePanel adds a Flow section that
narrates the path through a clicked node (flowNarrative); default copy is
mode-aware. Edge legend rounded out (editing/touches).
- GraphView polls every 5s and diffs (positions preserved), + ws /api/events nudge.
Stale selection (node gone across a poll) dropped so the canvas can't dim entirely.
Backend (surgical — main's materializer + buildLoop kept):
- live.ts: headline metric cards derived from the FINAL de-noised graph (Open risk
paths = distinct collision files; Learned owners = distinct owner engineers)
instead of raw collision-signature / accepted-outcome counts that inflate with
test churn (50 -> 4 risk files, 16 -> 1 owner on live). buildLoop untouched.
- demo.ts: metrics realigned to the demo graph (3 owners / 1 risk path / 100%).
Verified: lint + -r typecheck + -r build pass; Playwright confirmed the dynamic
graph (ticks on load, draggable), the loop rail (5 steps, ADAPT active) and
activity stream rendering main's shapes, honest metrics (3/1/100%), and the flow
narrative per node kind — zero page errors.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
sb-iam
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