2026-02-28T02-08-06_auto_memory/memories.db-wal, memory/2026-02-28-ig-dm-wh

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Nicholai Vogel 2026-02-27 19:08:06 -07:00
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# 2026-02-27 Session Notes
## IG DM Wholesale Automation — Deliverable Validation
Nicholai reviewed and validated the IG DM Wholesale Automation project against the client brief. The project implements a 7-step buyer journey with automation across Make scenarios, Airtable, ManyChat, and Shopify.
## Deliverables Status
All primary deliverables are complete and meet brief requirements:
**Airtable Base** — 5 tables (Retailers, Orders, Message Log, Follow-up Queue, Automations Log) with 7 pipeline stages matching brief exactly. Views include kanban board, follow-up queue, draft order readiness, error tracking.
**Make Scenarios** — 5 scenarios implement the full flow: (1) reply processing with intent classification, (2) email/shipping info extraction, (3) Shopify draft order creation with starter pack templates, (4) payment detection and pipeline update, (5) follow-up engine with daily reminders and reorder nudges.
**Shopify Integration** — Draft order automation with 3 starter pack templates (Best Sellers, New Arrivals, Full Range Sample). Webhook detection for payment completion. Invoice generation and DM/email sending.
**ManyChat Flows** — Inbound reply routing with keyword triggers, quick-reply buttons, 24-hour automation pause on live chat takeover. 14 response templates covering all buyer journey stages.
**Documentation** — SETUP.md (6-step setup + testing checklist), architecture.md (ASCII flow diagram, 6-step journey, tech stack), README.md.
## Gaps Identified
1. Loom walkthrough not in repo (expected as separate deliverable)
2. Placeholder values in starter-pack-templates.json need real Shopify variant IDs/SKUs/prices before deployment
3. No explicit error alerting configured (Automations Log captures but doesn't notify)
4. Brandboom link is static/hardcoded, not dynamically looked up
5. No fallback for messages outside Instagram's 24-hour window (acknowledged but not implemented)
## Testing Plan
End-to-end testing requires 3 phases: OpenAI prompt validation, component integration, edge cases. Detailed test cases documented for all 4 AI components (intent classifier, info extractor, DM drafter, recommendation engine).

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