feat(escalations): magic-moment 3-option CTA + claim 500 fix

- HandoffContextScreen: 3-option layout (Continue/AI analysis/Own thing)
  with hasTaskLane, activeOptionKey, spinner/disabled states
- AssistantChatPage: wire up handleContinue, handleAIAnalysis, handleOwnThing
  handlers; chip detail expansion inline with copy-button fix; post-escalation
  redirect to dashboard on ConcludeSessionModal close
- TaskLane: fix async copy button (await + execCommand fallback + copiedKey
  visual feedback); whitespace-pre-wrap on command blocks
- Fix 500 on claim: Pydantic v2 model_validate() + model_copy(update={})
  (was passing update= kwarg directly which v2 rejects)
- HandoffResponse schema: handed_off_by_name field

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

backend/app/services/flowpilot_engine.py

@@ -913,6 +913,41 @@ async def generate_status_update(
     """Generate a status update for ticket notes, client communication, or email draft."""
     session = await _load_session(session_id, user_id, db)
 
+    # For escalation/ticket_notes, return the pre-generated handoff prose immediately
+    # if enrich_escalation_async has already populated it. This eliminates the
+    # redundant Sonnet re-summarization on every "Ticket Notes" click.
+    if request.context == "escalation" and request.audience == "ticket_notes":
+        from app.models.session_handoff import SessionHandoff
+
+        handoff_q = await db.execute(
+            select(SessionHandoff)
+            .where(
+                SessionHandoff.session_id == session_id,
+                SessionHandoff.intent == "escalate",
+            )
+            .order_by(SessionHandoff.created_at.desc())
+            .limit(1)
+        )
+        escalation_handoff = handoff_q.scalar_one_or_none()
+        saved_data = (
+            escalation_handoff.ai_assessment_data or {}
+        ) if escalation_handoff else {}
+        prose = saved_data.get("summary_prose") or (
+            escalation_handoff.ai_assessment if escalation_handoff else None
+        )
+        if prose:
+            return StatusUpdateResponse(
+                content=prose,
+                audience=request.audience,
+                length=request.length,
+                context=request.context,
+                session_status=session.status,
+                steps_completed=session.step_count or 0,
+                time_spent_display=None,
+                client_name=None,
+                generated_at=datetime.now(timezone.utc),
+            )
+
     # Build conversation summary from session steps
     steps_summary = []
     for step in sorted(session.steps, key=lambda s: s.step_order):