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Product Roadmap

Current State (2026-02-26)

CareSupport runs as a single-family pilot (Kano family). One care recipient (Degitu), one registered member (Liban), SMS via Linq/iMessage. Files are the database. No self-service onboarding. No multi-family routing beyond directory scanning.

What's Proven

  • 13-step SMS pipeline works end-to-end
  • Approval gating blocks sensitive changes until confirmed
  • PHI filtering, role-based access, audit logging all mechanical
  • Family.md + member profiles update through conversation
  • Outreach queuing (needs_outreach → Linq create_chat) works

What's Broken

  • Agent asks excessive clarifying questions instead of acting on clear input
  • 6 family members listed with phone numbers → 0 added to routing.json
  • Pending approval for care recipient update → user hasn’t been prompted to confirm
  • No per-family learning — corrections are global only
  • Relationship context stored as single field (to care recipient), not member-to-member

Implementation Strategy: Land → Pro → Agency

The Expansion Sequence: Land with Family → pull in Pro via invites → bring in Agency with shared-timeline proof. Seed each step with clear wins.
1

Phase 1: Land with Family

Prove coordination value inside a single Family Circle
2

Phase 2: Pull in Pro

Enable a professional to coordinate multi-family work while plugging into the family’s Circle
3

Phase 3: Bring in Agency

Demonstrate value to the agency without heavy integration

Phase 0: Fix the Pilot (Now)

Goal

Make the Kano family work properly before scaling anything.

Conversation Skills

What: Add skill.md — social skills that guide conversation flowWhy: Agent should prompt “Want me to invite them?” after receiving member list, not ask 3 more clarifying questions

Context Prioritization

What: Define mandatory vs optional fields in family.md and member.mdWhy: Agent wastes turns asking for blood type when it should be saving the 6 phone numbers it already has

Per-Family Lessons

What: Add families/{id}/lessons.md — local correctionsWhy: “Degitu prefers Auntie” shouldn’t leak to other families; “always confirm before adding members” should be global

Resolve Pending State

What: Clear the pending approval backlog, add the 6 family membersWhy: The pilot is stuck because the agent over-gated a straightforward update

Phase 1: Land with Family (Rob’s Network)

Timeline: 0–30 Days

Goal: Prove NHS lift in a real Family Network (Rob + Marta), then expand Pro → Agency with clear wins.

Setup

  • Create Family Circle
  • Set Policy Pack Family.Pro-Integrated
  • Set coverage window
  • Import calendars
  • Invite close supporters

Quick Wins (≤7 days)

Baseline Metrics

Baseline Network Health Score (NHS) auto-generated

First Gap Alert

First gap alert detected and resolved

First Handoff

Handoff summary captured at least once

Coverage Improvement

Coverage % +10pp vs. baseline OR gap minutes/week −20%

Features to Emphasize

  • Today/Timeline view
  • Task management
  • Schedule conflict detection
  • Availability rules
  • Handoff summaries

Complete Single-Family Depth

ItemSuccess Metric
All members registered7/7 people in routing.json with profiles; all can text CareSupport and get context-aware responses
Transportation scheduleMon–Fri pickup/dropoff in family.md This Week section; schedule populated, visible to drivers
First outreachCareSupport texts Solan or Yada about a shift; outreach sent, reply received, logged
First handoffDriver change captured and next driver notified; handoff summary in timeline
NHS baselineNetwork Health Score v0 calculated; Coverage %, gap minutes, time-to-fill measurable
Trigger to Phase 2: Uncovered hours >15% OR recurring tasks require pro skills → Invite a Pro nudge.

Phase 2: Pull in Pro via Invites (CareGiver OS)

Timeline: 31–60 Days

Goal: Enable a professional to coordinate multi-family work while plugging into the family’s Circle.

Flow

1

Family Invites

Family → Invite Pro (SMS/email)
2

Pro Joins

Pro joins CareGiver OS → sets availability
3

Receives Assignments

Pro receives assignments → logs sessions
4

Sends Summaries

Pro sends visit summaries → family sees in Timeline

Quick Wins (≤7 days)

First Session Logged

First session logged & summarized; family sees it in Timeline

Fast Gap Fill

Time-to-fill for next gap < 24h

Adherence Improvement

Adherence improvement for at least one med/appointment

First Payout

Pro issues first invoice/payout

Incentives

  • 14-day Pro trial
  • Referral credit
  • “Verified Pro Profile”

Multi-Family Architecture

Make the system capable of running 2+ families without operator intervention.
ItemChallenge
Family creation CLIpython scripts/create_family.py --name "tefera" --coordinator "+1..." — Seed routing.json, family.md, member profile from templates
SMS self-service signupNew number texts in → “Start a care network” flow — Need to distinguish new family vs existing member on unknown number
Cross-family isolationOne member in 2 families (e.g., caregiver serves multiple) — routing.json currently maps phone → one family. Need multi-family resolution
Global lesson graduationLocal lesson appears in 2+ families → promote to global — Need a review mechanism, not automatic (family-specific context could be wrong globally)
Trigger to Phase 3: Pro/Family references an agency OR backup staffing need emerges → Share Timeline with Agency prompt.

Phase 3: Bring in Agency via Shared-Timeline Proof

Timeline: 61–90 Days

Goal: Demonstrate value to the agency without heavy integration.

Flow

1

Invite Agency

Invite agency coordinator → Linked Circle view (read/write per policy)
2

Minimal Adapter

Minimal adapter (CSV/ICS/API lite) → shifts appear in family view
3

Incident Routing

Incidents route back to agency coordinator
4

Measure NHS Lift

Agency sees NHS lift and handoff quality metrics

Quick Wins (≤14 days)

Reduced Calls

Coordinator calls/emails reduced for that family

Better Coverage

Coverage % up; support tickets down

NHS Improvement

Agency sees NHS lift and handoff quality metrics

Next Steps

Offer deeper adapters (HR/payroll/EVV) based on demonstrated ROI

Pro Integration Features

FeatureDescription
Pro invite flowFamily coordinator invites pro → pro joins with scoped access
Multi-family dashboardPro sees schedule across families they serve
Session loggingPro logs visits, family sees summaries in timeline
Availability rulesPro sets hours, system prevents invalid assignments

Exit Criteria (90 Days)

Family NHS

NHS ≥ +10 over baseline and sustained 2+ weeks

Pro Retention

30-day retention ≥ 70%; ≥ 80% sessions with handoffs

Agency Impact

Pilot demonstrates measurable reductions in calls/tickets

KPI Ladder by Stage

Phase 1: Family

  • NHS Delta: Improvement over baseline
  • Gap minutes ↓: Reduction in uncovered time per week
  • Time-to-first-resolution: Speed of gap closure
  • # helpers activated: Number of team members actively using system

Phase 2: Pro

  • Time-to-first-session: Speed from invite to first logged session
  • % visits with handoffs: Quality of care continuity
  • Pro 30-day retention: Stickiness of CareGiver OS
  • Invoice cycle time: Business operations efficiency

Phase 3: Agency

  • Linked clients count: Number of families connected
  • Support contacts ↓: Reduction in coordinator burden
  • Coverage % ↑: Improvement in shift coverage
  • NPS lift: Partner satisfaction improvement

Scaling Challenges

Challenge 1: Scaling Families

Problem: Every new family requires manual directory creation, routing.json seeding, family.md templating, first-message-via-Linq to establish chat_id. This is 6 manual steps that require operator knowledge.Why it’s hard:
  • Phone number is the primary key, but one person can be in multiple families
  • Chat_id (Linq’s UUID) is only known after first message — chicken-and-egg
  • Template family.md has sections that may not apply to every family (not everyone tracks medications)
  • No rollback if onboarding fails halfway
Constraints:
  • Must work over SMS (no web UI for onboarding)
  • Must preserve file-as-database architecture (no external DB)
  • Must maintain approval gating for sensitive data from day one
  1. CLI tool first (operator-assisted, Phase 2)
  2. SMS self-service second (fully automated, Phase 2 stretch)
  3. Web dashboard third (Phase 3+, only if needed)

Challenge 2: Context Explosion

Problem: As families grow, the amount of context loaded per message grows. family.md Current section has a 2000-token soft limit, but with 7+ members, active medications, and weekly schedules, it’ll exceed that.Why it’s hard:
  • Every message loads Current section in full
  • Agent needs enough context to be useful but not so much it hallucinates
  • Different messages need different context (schedule question vs medication question)
Proposed approach: Mandatory/optional framework and intent-based context loading.

Challenge 3: Conversation Quality at Scale

Problem: CareSupport’s conversation quality depends on prompt engineering in SOUL.md + capabilities.md. As we add families with different dynamics, a single prompt may not generalize.Why it’s hard:
  • Each family has different communication norms
  • Some families are terse, some are verbose
  • Cultural context matters (naming conventions, family structure, communication expectations)
  • Global lessons from one family may not apply to another
Proposed approach: Per-family skill.md for conversation patterns + per-family lessons.md for corrections. Global lessons only for universal patterns.

Network Health Metrics

North Star: Network Health Score (NHS)

Definition: Single score per network to prove coordination value

Coverage %

Percentage of target coverage window actually covered

Gap Minutes

Total uncovered minutes per week

Time-to-Fill

Median time from gap detection to resolution

Adherence

Medication and appointment adherence rates

Handoff Quality

Percentage of shifts with proper handoff documentation

Coordination Time

Coordinator time saved on scheduling and follow-ups

Product KPIs

  • NHS delta over baseline: Primary success metric
  • Network NPS (coordination lead view): Satisfaction measurement
  • CareGiver OS retention: Professional stickiness
  • Partner retention (platform/agency): B2B success

Technology Roadmap

Now: Lighthouse Pilot

  • Coverage workspace
  • Gap/conflict detection
  • Handoffs
  • Availability rules
  • Decision trace capture

Next: Multi-Family Operations

  • Ranked proposals
  • Fairness heatmaps
  • Opt-in automations
  • Precedent search UI

Later: Advanced Capabilities

  • External calendar & wearable signals
  • Proactive “coverage health” alerts
  • Community routing
  • Simulation queries

Risks & Mitigations

RiskWhy It MattersMitigation
Cold start in multi-sided networkNeed families and pros and partnersStage GTM; seed Family Hubs; recruit pros via value props; pilot partners
Integration frictionAgencies/marketplaces are busy, legacy stacksProvide adapters, playbooks, commercial incentives (retention/NPS lift)
Compliance variability by stateProduct behavior must adaptPolicy graph + jurisdiction packs; local counsel & templates
Perception as competitorPartners may fear overlapStrict neutral posture; published interoperability charter; white-label options
Data trust & privacyMust be trusted by families and prosTransparent controls, consent receipts, minimal data exposure by default

Strategic FAQ

We equip each care network with network-specific infrastructure (Circle + Policy Pack) and prove value via a Network Health Score. We expand Land → Pro → Agency with clear wins at each step.
No. We’re the coordination layer used after the match and during the relationship. Families, independent pros, agencies, and platforms each get tools tuned to their network.
It elevates independent caregivers into technology-enabled professionals who can run multi-family practices, while linking cleanly into family circles and agency views.
B2C (Family), B2Pro (CareGiver OS), B2B (Agency), plus Platform APIs. All mapped to demonstrated NHS improvements.
Measurable NHS lift (fewer gaps, faster fills, better handoffs), reduced coordination burden, and simple adapters (CSV/ICS/API-lite) with a path to deeper integrations.

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