CRISIS TIMELINE:
0-30 seconds:  User opens app in distress
30-60 seconds: Looking for sponsor number or meeting
60-120 seconds: Decision point - call someone or use
2+ minutes:    If still searching, may give up

EVERY SECOND OF LOAD TIME = LIVES AT RISK

Next.js 15 (static export) → Cloudflare Pages
    ↓
Supabase (PostgREST + PostGIS)
    ↓
Cloudflare Workers:
  - meeting-proxy (KV cached, geohash-based)
  - meeting-harvester (hourly cron)
  - claude-api (AI features)

User location → Geohash (3-char ~150km cell)
    → KV cache lookup (edge, ~5ms)
    → Cache HIT: Return immediately
    → Cache MISS: Supabase RPC find_current_meetings
        → PostGIS ST_DWithin query
        → Store in KV, return

User opens contacts → Local IndexedDB first
    → Show cached contacts instantly
    → Background sync with Supabase
    → Update UI if changes

Open check-in → Pre-rendered form shell
    → Load previous patterns async
    → Submit optimistically

// Service Worker must cache:
const CRISIS_CRITICAL = [
  '/contacts',           // Sponsor phone numbers
  '/safety-plan',        // User's safety plan
  '/meetings?saved=true', // Saved meetings list
  '/crisis',             // Crisis resources page
];

// These MUST work with zero network:
// 1. View sponsor contacts
// 2. View safety plan
// 3. View saved meetings (even if stale)
// 4. Record check-in (sync when online)

// RED FLAGS (surface help proactively):
const CRISIS_INDICATORS = {
  anger_spike: 'HALT angry score jumps 3+ points',
  ex_mentions: 'Mentions ex-partner 3+ times in week',
  isolation: 'No check-ins for 3+ days after daily streak',
  time_distortion: 'Check-ins at unusual hours (2-5am)',
  negative_spiral: 'Consecutive declining mood scores',
};

// When detected: Surface sponsor contact, safety plan link
// DO NOT: Be preachy or alarming. Gentle nudge only.

-- Detect concerning patterns
SELECT user_id,
  AVG(angry_score) as avg_anger,
  AVG(angry_score) FILTER (WHERE created_at > NOW() - INTERVAL '3 days') as recent_anger,
  COUNT(*) FILTER (WHERE EXTRACT(HOUR FROM created_at) BETWEEN 2 AND 5) as late_night_checkins
FROM daily_checkins
WHERE created_at > NOW() - INTERVAL '30 days'
GROUP BY user_id
HAVING AVG(angry_score) FILTER (WHERE created_at > NOW() - INTERVAL '3 days') >
       AVG(angry_score) + 2;

// Client-side (log to analytics)
const PERF_METRICS = {
  ttfb: 'Time to First Byte',
  fcp: 'First Contentful Paint',
  lcp: 'Largest Contentful Paint',
  tti: 'Time to Interactive',

  // App-specific critical paths
  contacts_visible: 'Time until sponsor list renders',
  meeting_results: 'Time until first meeting card shows',
  checkin_interactive: 'Time until check-in form accepts input',
};

// Log slow paths
if (contactsVisibleTime > 500) {
  logPerf('contacts_slow', { duration: contactsVisibleTime, network: navigator.connection?.effectiveType });
}

# scripts/perf-audit.sh - Run in CI
lighthouse https://sobriety.tools/meetings --output=json --output-path=./perf.json
SCORE=$(jq '.categories.performance.score' perf.json)
if (( $(echo "$SCORE < 0.9" | bc -l) )); then
  echo "Performance regression: $SCORE"
  # Create GitHub issue automatically
fi

// Run hourly via Cloudflare Worker cron
async function performanceAudit() {
  const checks = [
    checkMeetingCacheHealth(),
    checkSupabaseQueryTimes(),
    checkStaticAssetSizes(),
    checkServiceWorkerCoverage(),
  ];

  const issues = await Promise.all(checks);
  const problems = issues.flat().filter(i => i.severity === 'high');

  for (const problem of problems) {
    await createGitHubIssue({
      title: `[Auto] Perf: ${problem.title}`,
      body: problem.description + '\n\n' + problem.suggestedFix,
      labels: ['performance', 'automated'],
    });
  }
}

// WRONG
const { data: contacts } = useQuery(['contacts'], fetchContacts);

// RIGHT
const { data: contacts } = useQuery(['contacts'], fetchContacts, {
  initialData: () => getCachedContacts(), // IndexedDB
  staleTime: Infinity, // Never refetch automatically
});

// Lazy load non-critical features
const JournalAI = dynamic(() => import('./JournalAI'), { ssr: false });
const Charts = dynamic(() => import('./Charts'), { loading: () => <ChartSkeleton /> });