Update agent

AGENTS.md

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+# MeetVault — Agent Guide
+
+## Repo layout
+
+```text
+MeetVault/
+├── Overview/          # Architecture docs, schema, data flow
+│   └── README.md
+├── Wireframes/         # Desktop client design notes
+│   └── Desktop/
+│       ├── Desktop_README.md
+│       └── Desktop-Demo/  # Runnable Tauri + React demo
+│           └── speech-engine/  # Local Whisper transcription engine
+```
+
+## Core architecture (remember this)
+
+- **User machine**: records audio/video, runs local Whisper for STT, sends transcript to backend. Keeps compute and cost on the device.
+- **Backend API**: auth, meeting metadata, presigned upload URLs, transcript ingestion, summarization jobs, task extraction, reminder scheduling.
+- **PostgreSQL**: structured app data + `processing_jobs` table used as a job queue (no external broker needed for MVP).
+- **SeaweedFS**: S3-compatible object storage for large media files.
+
+## PostgreSQL gotchas
+
+### Enable UUID generation first
+
+```sql
+CREATE EXTENSION IF NOT EXISTS pgcrypto;
+```
+
+### Always set `updated_at` manually
+
+PostgreSQL does not auto-update it. Create a shared trigger function and apply to every table that tracks changes:
+
+```sql
+CREATE OR REPLACE FUNCTION set_updated_at()
+  RETURNS TRIGGER AS $$
+BEGIN
+    NEW.updated_at = NOW();
+    RETURN NEW;
+END;
+$$ LANGUAGE plpgsql;
+
+-- then attach per-table triggers, e.g.:
+CREATE TRIGGER trg_meetings_updated_at
+  BEFORE UPDATE ON meetings FOR EACH ROW EXECUTE FUNCTION set_updated_at();
+```
+
+### Job queue pattern (no external broker)
+
+Workers pick jobs with this exact query:
+
+```sql
+SELECT *
+FROM processing_jobs
+WHERE status = 'queued'
+  AND available_at <= NOW()
+ORDER BY priority DESC, created_at
+FOR UPDATE SKIP LOCKED
+LIMIT 1;
+```
+
+Key indexes for workers:
+
+```sql
+CREATE INDEX idx_schedules_due ON meeting_schedules(status, scheduled_at);
+CREATE INDEX idx_processing_jobs_queue ON processing_jobs(status, available_at, priority DESC);
+```
+
+### SeaweedFS object paths
+
+Files live under: `meeting-storage/users/{user_id}/meetings/{meeting_id}/original/`
+
+## Testing flow
+
+1. Run the desktop demo locally (Tauri + React) to verify UI and local transcription without backend dependencies.
+2. Spin up PostgreSQL, run the schema SQL from `Overview/README.md`, then start the backend API.
+3. End-to-end: record a short clip on the desktop client → upload via presigned URL → ingest transcript → trigger summarization job → verify summary appears in DB.
+
+## What is intentionally out of scope for MVP
+
+- Kafka, Elasticsearch, Kubernetes, vector DBs, Redis (unless job volume grows), microservices. PostgreSQL + SeaweedFS + workers is sufficient.