feat(graph): dynamic force-directed Team-memory graph + learning-loop & activity rails

Rebuild the live "Team memory" view so the light/real-data version matches the
dark Bauhaus mock and the graph is genuinely DYNAMIC instead of dead static columns.

Frontend (frontend/src/components/graph/*, composed into GraphView.tsx):
- forceSim.ts: a tiny dependency-free force layout (charge repulsion, link springs,
  centroid recentering + gentle pull, 2-pass collision, bounds clamp, alpha anneal).
  No d3-force dependency added — keeps the shared pnpm-lock untouched so CI's
  frozen-lockfile install and the deploy path are unaffected.
- GraphCanvas.tsx: SVG render driven by the sim — draggable + pinnable nodes
  (double-click to release), curved edges that fan parallel pairs, weight-sized
  geometric node shapes, fade-in on new nodes/edges, animated learned_from dash,
  risk-path lighting with the rest dimmed, label collision-avoidance.
- MetricsRail / LearningLoop / ActivityStream / SelectedNodePanel / encoding.ts:
  the mock's rails + stream + detail panel, light shadcn (ToggleGroup, ScrollArea,
  Badge, Button) on theme tokens; only the SVG is bespoke.
- GraphView polls /api/pods/:id/graph every 5s and diffs (positions preserved across
  refreshes), with a best-effort ws /api/events nudge. A stale selection (node gone
  across a poll) is dropped so the canvas can't dim entirely.

Backend (additive — materializer de-noise untouched):
- live.ts: buildLoop() (observe→store→predict→outcome→adapt counts, deepest-recent
  stage active) and buildActivity() (time-sorted typed feed, same isFilePath /
  ENGINEER_NOISE / signature de-noise) emitted alongside nodes/edges/metrics.
- demo.ts: fallback loop + activity so the panels render on the demo path.
- shared/src/graph.ts: additive optional PodGraph.loop / .activity + LearningStage /
  ActivityEvent types.

Verified: pnpm lint + -r typecheck + -r build pass; Playwright on the dev build
confirmed force layout (distinct positions, ticks on load under StrictMode), drag,
risk-mode dimming (opacity 0.14), selection panel, legend, and no overlaps on both
the clean demo and the 31-node live hairball.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

backend/src/graph/demo.ts

@@ -8,9 +8,45 @@ import type { PodGraph } from '@podman/shared';
  * auth* — is the continual-learning story the demo lights up.
  */
 export function createDemoPodGraph(podId: string): PodGraph {
+  const base = Date.now();
+  const at = (secAgo: number): string => new Date(base - secAgo * 1000).toISOString();
   return {
     podId,
     generatedAt: new Date().toISOString(),
+    loop: [
+      { key: 'observe', title: 'OBSERVE', value: '5', detail: '~5/s vision contexts', active: false },
+      { key: 'store', title: 'STORE', value: '124', detail: 'memory vectors · Atlas', active: false },
+      { key: 'predict', title: 'PREDICT', value: '2', detail: 'collisions flagged', active: true },
+      { key: 'outcome', title: 'OUTCOME', value: '1/0', detail: 'accepted · dismissed', active: false },
+      { key: 'adapt', title: 'ADAPT', value: '5', detail: 'learned owners', active: false },
+    ],
+    activity: [
+      {
+        id: 'demo-learn',
+        at: at(20),
+        kind: 'learned_from',
+        text: 'Memory updated: Karti owns auth.ts (confidence ↑)',
+      },
+      { id: 'demo-out', at: at(24), kind: 'outcome', text: 'Intervention accepted by the pod' },
+      {
+        id: 'demo-warn',
+        at: at(40),
+        kind: 'warns',
+        text: 'PodMan: "Karti & Yahya are both in auth.ts — open a sync PR?" → card sent',
+      },
+      {
+        id: 'demo-col',
+        at: at(58),
+        kind: 'collision',
+        text: 'Critical overlap on auth.ts · Karti + Yahya',
+      },
+      {
+        id: 'demo-edit',
+        at: at(72),
+        kind: 'editing',
+        text: 'Yahya opened auth.ts — unpushed changes',
+      },
+    ],
     metrics: [
       {
         label: 'Learned owners',

backend/src/graph/live.ts

@@ -6,6 +6,13 @@ import type {
   PodGraphNodeKind,
   PodGraphEdgeKind,
   PodGraphNodeStatus,
+  LearningStage,
+  LearningStageKey,
+  ActivityEvent,
+  EngineerContext,
+  Collision,
+  Intervention,
+  InterventionOutcome,
 } from '@podman/shared';
 import { collections, getGitStates, getDb } from '../memory/db.js';
 
@@ -148,6 +155,185 @@ function layout(nodes: PodGraphNode[]): void {
 
 const SEVERITY_WEIGHT: Record<string, number> = { info: 0.4, warn: 0.7, critical: 1 };
 
+/** Parse any timestamp-ish value to epoch ms (0 when missing/unparseable). */
+function ms(t: string | Date | null | undefined): number {
+  if (!t) return 0;
+  const v = new Date(t).getTime();
+  return Number.isFinite(v) ? v : 0;
+}
+
+const OBSERVE_WINDOW_MS = 60_000;
+
+/**
+ * Live counts for the learning-loop rail (observe→store→predict→outcome→adapt).
+ * The "active" stage is the one whose latest underlying event is most recent —
+ * with deeper stages winning ties so the rail lights up at the furthest point
+ * the pod reached this session. Additive: derived from already-fetched docs.
+ */
+function buildLoop(opts: {
+  now: number;
+  observations: EngineerContext[];
+  collisions: Collision[];
+  outcomes: InterventionOutcome[];
+  riskPaths: number;
+  vectorCount: number;
+  learnedOwners: number;
+}): LearningStage[] {
+  const { now, observations, collisions, outcomes, riskPaths, vectorCount, learnedOwners } = opts;
+
+  const recentObs = observations.filter((o) => now - ms(o.observedAt) < OBSERVE_WINDOW_MS).length;
+  const rate = (recentObs / 60).toFixed(1);
+  const accepted = outcomes.filter((o) => o.accepted).length;
+  const dismissed = outcomes.filter((o) => !o.accepted).length;
+
+  // Latest event time per stage; `store` sits just behind `predict` so a shared
+  // collision timestamp resolves to PREDICT rather than STORE.
+  const latestObs = Math.max(0, ...observations.map((o) => ms(o.observedAt)));
+  const latestCol = Math.max(0, ...collisions.map((c) => ms(c.detectedAt)));
+  const latestOut = Math.max(0, ...outcomes.map((o) => ms(o.recordedAt)));
+  const latestAdapt = Math.max(
+    0,
+    ...outcomes.filter((o) => o.accepted && o.wasRealCollision).map((o) => ms(o.recordedAt)),
+  );
+
+  const refs: Array<[LearningStageKey, number]> = [
+    ['observe', latestObs],
+    ['store', latestCol ? latestCol - 1 : 0],
+    ['predict', latestCol],
+    ['outcome', latestOut],
+    ['adapt', latestAdapt],
+  ];
+  let activeKey: LearningStageKey = 'observe';
+  let best = 0;
+  for (const [k, t] of refs) {
+    if (t > 0 && t >= best) {
+      best = t;
+      activeKey = k;
+    }
+  }
+
+  const stages: Array<Omit<LearningStage, 'active'>> = [
+    { key: 'observe', title: 'OBSERVE', value: String(recentObs), detail: `~${rate}/s vision contexts` },
+    { key: 'store', title: 'STORE', value: String(vectorCount), detail: 'memory vectors · Atlas' },
+    {
+      key: 'predict',
+      title: 'PREDICT',
+      value: String(riskPaths),
+      detail: `${riskPaths === 1 ? 'collision' : 'collisions'} flagged`,
+    },
+    { key: 'outcome', title: 'OUTCOME', value: `${accepted}/${dismissed}`, detail: 'accepted · dismissed' },
+    {
+      key: 'adapt',
+      title: 'ADAPT',
+      value: String(learnedOwners),
+      detail: `learned owner${learnedOwners === 1 ? '' : 's'}`,
+    },
+  ];
+  return stages.map((s) => ({ ...s, active: s.key === activeKey }));
+}
+
+/**
+ * Merge + time-sort recent events into the activity stream feed. Reuses the same
+ * de-noise (isFilePath / ENGINEER_NOISE / signature collapse) as the graph so
+ * the feed never shows junk paths or test-artifact engineers. Capped to 8.
+ */
+function buildActivity(opts: {
+  observations: EngineerContext[];
+  collisions: Collision[];
+  interventions: Intervention[];
+  outcomes: InterventionOutcome[];
+  ownership: Record<string, string>;
+}): ActivityEvent[] {
+  const { observations, collisions, interventions, outcomes, ownership } = opts;
+  const cleanEng = (n: string): boolean => Boolean(n) && !ENGINEER_NOISE.test(n);
+  const out: ActivityEvent[] = [];
+
+  // editing — newest observation per (engineer, file); observations arrive desc.
+  const seenEdit = new Set<string>();
+  for (const o of observations) {
+    if (!o.engineerId || !cleanEng(o.engineerId)) continue;
+    const file = o.currentFile ? normalizeFile(o.currentFile) : '';
+    if (!isFilePath(file)) continue;
+    const key = `${o.engineerId.toLowerCase()}|${file}`;
+    if (seenEdit.has(key)) continue;
+    seenEdit.add(key);
+    out.push({
+      id: `edit:${o.engineerId}:${file}`,
+      at: o.observedAt,
+      kind: 'editing',
+      text: `${o.engineerId} opened ${shortLabel(file)}${
+        o.hasUnpushedChanges ? ' — unpushed changes' : ''
+      }`,
+    });
+  }
+
+  // collision — collapse by signature, newest first.
+  const seenCol = new Set<string>();
+  for (const c of collisions) {
+    const file = normalizeFile(c.file);
+    if (!isFilePath(file)) continue;
+    const sig = (c as { memorySignature?: string }).memorySignature ?? `${file}#${c.symbol ?? ''}`;
+    if (seenCol.has(sig)) continue;
+    seenCol.add(sig);
+    const engs = c.engineers.filter(cleanEng);
+    if (!engs.length) continue;
+    out.push({
+      id: `col:${c.id}`,
+      at: c.detectedAt,
+      kind: 'collision',
+      text: `${c.severity === 'critical' ? 'Critical overlap' : 'Overlap'} on ${shortLabel(
+        file,
+      )} · ${engs.join(' + ')}`,
+    });
+  }
+
+  // warns — interventions PodMan raised.
+  for (const iv of interventions) {
+    if (!iv.message) continue;
+    const msg = iv.message.length > 64 ? `${iv.message.slice(0, 61)}…` : iv.message;
+    out.push({
+      id: `warn:${iv.id}`,
+      at: iv.createdAt,
+      kind: 'warns',
+      text: `PodMan: "${msg}" → card sent`,
+    });
+  }
+
+  // outcome + learned_from — the supervised learning beat.
+  const colById = new Map(collisions.map((c) => [c.id, c]));
+  const ivById = new Map(interventions.map((i) => [i.id, i]));
+  for (const o of outcomes) {
+    if (!o.accepted) continue;
+    out.push({
+      id: `out:${o.interventionId}`,
+      at: o.recordedAt,
+      kind: 'outcome',
+      text: 'Intervention accepted by the pod',
+    });
+    if (!o.wasRealCollision) continue;
+    const iv = ivById.get(o.interventionId);
+    const col = iv ? colById.get(iv.collisionId) : colById.get(o.collisionId);
+    if (!col) continue;
+    const file = normalizeFile(col.file);
+    if (!isFilePath(file)) continue;
+    const owner =
+      (o as { learnedOwner?: string }).learnedOwner ??
+      ownership[file] ??
+      col.engineers.find(cleanEng) ??
+      col.engineers[0];
+    if (!owner) continue;
+    out.push({
+      id: `learn:${o.interventionId}`,
+      at: o.recordedAt,
+      kind: 'learned_from',
+      text: `Memory updated: ${owner} owns ${shortLabel(file)} (confidence ↑)`,
+    });
+  }
+
+  out.sort((a, b) => ms(b.at) - ms(a.at));
+  return out.slice(0, 8);
+}
+
 export async function materializePodGraph(podId: string): Promise<PodGraph | null> {
   const c = await collections();
   const db = await getDb();
@@ -390,11 +576,46 @@ export async function materializePodGraph(podId: string): Promise<PodGraph | nul
     },
   ];
 
+  // Stored vectors for the STORE stage: prefer a real memory_vectors count,
+  // fall back to collisions carrying an embedding, then to collision count.
+  let vectorCount = 0;
+  try {
+    vectorCount = await db.collection('memory_vectors').countDocuments({ podId });
+  } catch {
+    /* memory_vectors is optional */
+  }
+  if (!vectorCount)
+    vectorCount = collisionDocs.filter(
+      (c) => (c as { embedding?: number[] }).embedding?.length,
+    ).length;
+  if (!vectorCount) vectorCount = collisionDocs.length;
+
+  const learnedOwners = Object.keys(ownership).length || acceptedReal;
+
+  const loop = buildLoop({
+    now,
+    observations,
+    collisions: collisionDocs,
+    outcomes: outcomeDocs,
+    riskPaths,
+    vectorCount,
+    learnedOwners,
+  });
+  const activity = buildActivity({
+    observations,
+    collisions: collisionDocs,
+    interventions: interventionDocs,
+    outcomes: outcomeDocs,
+    ownership,
+  });
+
   return {
     podId,
     generatedAt: new Date().toISOString(),
     nodes,
     edges: [...b.edges.values()],
     metrics,
+    loop,
+    activity,
   };
 }