resolutionflow/.ai/HANDOFF.md

HANDOFF.md

Last updated: 2026-04-29 04:30 EDT

Active task: Escalation Mode wedge — AI generation consolidation. Full status + design in CURRENT_TASK.md. The wedge demo is demo-blocked by an empty AI assessment that didn't fix with a timeout bump. Architectural cause: 3 redundant AI calls per escalation; the right fix is to consolidate.

Branch: feat/escalation-metric-endpoint at 0d1b305. Pushed to origin. Draft PR #155 open.

Where the previous session ended

Live QA bash on the wedge demo. Branch state: 4 commits added this session (0f00ee5, 665530f, b7d7ff0, 0d1b305).

Confirmed working in browser:

• Junior escalates → senior bell-icon notification
• Senior Pick Up → magic-moment screen with handoff data
• Senior Start Here → chat surface loads with conversation history (0d1b305 fixed the selectChat-gating bug — was rendering blank before)
• Sidebar shows picked-up session with "Escalated" pill (0d1b305's loadChats() after claim)
• Suggested-step chips render below the composer
• Unread 6px dot on queue cards persists across refresh
• Task-lane regression killed — no stale flash on new sessions
• Enter-to-submit (Shift+Enter for newline) on EscalateModal and ConcludeSessionModal
• PendingEscalations rows on dashboard expand to show escalation reason + step count + ticket #

Active blocker:

• AI assessment never populates on the magic-moment screen. Bumping the timeout 15s → 45s in 0d1b305 did not fix it in the field. Backend logs from earlier in session showed Sonnet timing out at 15s; the assumption was the call would complete with more headroom, but live test still empty. May be a different failure mode (assessment generating but the bus event firing with has_assessment: false, or the frontend subscription not refetching, or the call genuinely failing past 45s).

Resume point — DO THIS NEXT

Replace the three redundant AI calls with a single structured generation. Full implementation plan in CURRENT_TASK.md under "Active task — AI generation consolidation." Summary:

1. Backend: Replace _generate_ai_assessment with one Sonnet call returning structured JSON: summary_prose (PSA-flavored) + what_we_know[] + likely_cause + suggested_steps[] + confidence. Persist to SessionHandoff. Use Anthropic structured output / tool-use to enforce the schema.
2. Backend: Make generate_status_update for audience='ticket_notes' / context='escalation' read the saved payload (instant). For client_update and email_draft, run a cheaper Haiku transformation over the saved prose, not a full re-summarization.
3. Backend: Stop calling _build_escalation_package_enhanced from the background path — overlapping content. Verify nothing downstream depends on the enhanced enriched payload before removing.
4. Frontend: HandoffContextScreen reads from the consolidated structured fields. ConcludeSessionModal's "Ticket Notes" button stops generating, just copies the saved prose. "Client Update" / "Email Draft" trigger the cheap transformation.
5. Test plan: magic-moment populates in ~5s. Token spend down ~60%. AI summary blocker resolved.

Implementation order (suggested): 1 → 4 (so the magic moment shows the new fields) → 2 → 3 (cleanup) → tests.

Watch-outs:

• Schema enforcement matters. Past calls returned freeform prose that doesn't parse into chips. Anthropic structured output / tool-use is the right tool.
• escalation_package JSON column has live data on existing sessions — keep it READABLE, just stop writing the enhanced payload from enrich_escalation_async. Dual-write the basic snapshot if downstream queue summaries need it.
• _generate_ai_assessment is stubbed in test_handoff_manager.py and test_session_handoffs_api.py via AsyncMock. Update test fixtures when renaming.
• The frontend assessment-ready SSE subscription (added in 0f00ee5) is fine as-is — it'll dispatch on the new event payload. No client changes for the live-refresh path.

Useful breadcrumbs

• AI assessment current impl: backend/app/services/handoff_manager.py — _generate_ai_assessment, _generate_ai_assessment_with_timeout, enrich_escalation_async.
• Status update current impl: backend/app/services/flowpilot_engine.py — generate_status_update, _build_status_update_prompt, _build_status_update_context.
• Enhanced package builder: backend/app/services/flowpilot_engine.py — _build_escalation_package_enhanced (line ~1694).
• Magic-moment screen: frontend/src/components/flowpilot/HandoffContextScreen.tsx.
• Conclude modal: frontend/src/components/assistant/ConcludeSessionModal.tsx — see handleGenerateStatusUpdate.
• Magic-moment integration + suggested-step chips: frontend/src/pages/AssistantChatPage.tsx.
• Test fixtures stubbing the assessment: backend/tests/test_handoff_manager.py, backend/tests/test_session_handoffs_api.py.

Watch-outs (general)

• Dev stack on this machine: backend :8000, frontend :5173, postgres :5433. All running via docker-compose. HMR works.
• Test users (Acme MSP shared account, password TestPass123!): engineer@resolutionflow.example.com (junior), teamadmin@resolutionflow.example.com (senior).
• The bus is acceptable for v1 pilot scale only (Railway single-replica). Redis pub/sub is the swap when horizontal scaling appears.
• streamEscalations doesn't drive token refresh on a mid-stream 401. Acceptable for v1.