ldy26098
/
BMAD-METHOD
mirror of https://github.com/bmad-code-org/BMAD-METHOD.git
1
0
Fork 0
Code Packages Projects Releases Wiki Activity
BMAD-METHOD/bmad/bmm/agents/hand-off/ARCHITECT-HANDOFF.md

6.0 KiB
Raw Blame History

ARCHITECT HANDOFF — Professional Journaling App (MVP)

Purpose

This document hands off full-stack planning to the architect for the AI-driven professional journaling MVP. It maps the six epics to system components, integration points, data models, security/privacy controls, infra choices, scalability considerations, and immediate engineering tasks.

Project constraints (reminder)

  • Budget: $5,000 for infra/API costs.
  • Timeline: 3 months, single developer (mobile-first).
  • Required integrations: OpenAI (generation), Whisper (transcription), LinkedIn publish + OAuth.
  • Privacy-first: local-first DB, opt-in cloud sync, ephemeral audio uploads, at-rest encryption for synced data.

Epic mapping & tech notes

  1. Epic: Capture & Local Storage (Issue #707)
  • Components: React Native (Expo) app, local SQLite/WatermelonDB, entry model, tag model, attachments storage.
  • Responsibilities:
    • Implement local DB schema; CRUD flows for entries.
    • Data export/import (user-facing).
    • Sync toggle and initial lightweight sync via Supabase or optional S3+signed-URL with user-provided token.
  • Data model (core):
    • Entry: id, createdAt, updatedAt, title, text, mood, tags[], attachments[], metadata (deviceId, language), anonymized flag
    • Attachment: id, entryId, type (audio/image), uri, uploadedAt (nullable)
  • Acceptance: CRUD + local search + basic list/filter by tag.
  1. Epic: Audio & Transcription (Issue #708)
  • Components: RN audio recorder, file store, serverless signed-upload, Whisper worker (serverless), client transcription UI.
  • Responsibilities:
    • Capture short audio (<=3 min), show levels, pause/resume.
    • Securely upload audio to serverless endpoint to request transcription.
    • Transcription callback writes transcription to DB and marks entry ready for generation.
  • Security: audio TTL on server (<=1hr), delete after successful transcribe, enforce consent prompt before recording.
  1. Epic: Generation & Drafting (Issue #709)
  • Components: serverless generation proxy (/generate-post), token controls, client draft editor, tone presets.
  • Responsibilities:
    • Serverless proxy to call OpenAI (or cheaper model) with prompt templates.
    • Provide variants (short, long) and allow user edit.
    • Track token usage per user and throttle; store generation metadata only when user opts-in.
  • Cost control: use smaller models for variants, limit to N generations/day per user.
  1. Epic: Publishing & Integrations (Issue #710)
  • Components: LinkedIn OAuth flow, publish endpoint, client fallback (share sheet), publish history model.
  • Responsibilities:
    • Implement OAuth on serverless, store token encrypted (or use LinkedIn short-lived tokens; prefer server proxy for publishing).
    • Provide a preview & explicit consent step before publishing.
  • Fallback: generate shareable text that opens LinkedIn app/share sheet.
  1. Epic: Privacy, Retention & Logging (Issue #711)
  • Components: consent logs, retention engine, soft-delete + purge jobs (serverless scheduled function), telemetry opt-in.
  • Responsibilities:
    • Implement user-level retention settings (default 90 days per decision doc) and provide per-entry delete.
    • Consent logging: record when user enabled publish, transcription, or cloud-sync.
    • Audit: minimal processing logs (no PII), store only necessary metadata for billing and debugging.
  1. Epic: Release & Ops (Issue #712)
  • Components: cost meter, quota enforcement, CI deploy for serverless, app store build pipeline (Expo EAS), README + runbooks.
  • Responsibilities:
    • Prepare release checklist, E2E QA plan, monitoring (error + usage), and an infra budget alert system.

Integration diagram (high-level)

  • Client (RN) ↔ Serverless proxy (auth, signed upload, generation proxy) ↔ External APIs (OpenAI, Whisper, LinkedIn, S3)
  • Local DB sync ↔ Optional cloud (Supabase or S3 + metadata store)

Infra recommendations

  • Serverless: Vercel or Netlify functions for dev; production host with simple billing (Vercel with limited usage or small Heroku dyno) to keep within $5K cloud spend.
  • Storage: S3-compatible (Backblaze B2 or AWS S3). Use signed URLs for upload; TTL and a serverless worker for transcription.
  • Database: Local SQLite (better performance on mobile) + optional Supabase Postgres for sync (opt-in). Encrypt fields at rest for cloud sync.
  • Secrets: store provider keys only on serverless; client never holds OpenAI/LinkedIn secrets.

Security & compliance

  • Record explicit consent for audio recording and LinkedIn publishing before initiating any recording or publish flow.
  • Implement local anonymization toggle that strips names/email patterns from text before sending to generation if enabled.
  • Retention/purge: implement scheduled job to delete files and rows after retention window; keep processing logs for 30 days.

Immediate engineering tasks (first 2 sprints) Sprint 0 (bootstrap)

  • Create RN Expo repo scaffold, set up local DB schema, implement project README and dev scripts (EAS + local build).
  • Wire GitHub CI for tests and release.
  • Create serverless-starter templates (signed-upload, transcribe-callback, generate-post, publish-linkedin).

Sprint 1 (core)

  • Implement local journaling UI: list, create, edit, tags, search.
  • Local DB integration & unit tests.
  • Basic settings & dev-mode API key input.

Sprint 2 (audio + transcription)

  • RN audio capture UI & client upload.
  • Serverless signed-upload + Whisper worker integration (test with small audio).
  • Client shows transcripts and allows edit/anonymize.

Operational notes

  • Rate-limit transcription/generation to avoid surprise bills.
  • Keep logs minimal and rotate frequently.
  • Test LinkedIn publish in a sandbox account before enabling to users.

Files & references

  • Hand-off docs: bmad/bmm/agents/hand-off/ includes PRD, USER-STORIES.md, SERVERLESS-API-SPEC.md, PROMPT-TEMPLATES.md, and this file.
  • Serverless starter: serverless-starter/ contains placeholder endpoints to copy into Vercel/Netlify.

Acceptance & sign-off

  • Architect to review infra choices, deployments, and cost model and confirm adjustments.
  • PM to confirm prioritization of P0 stories and owners.